photokin

Run scanned photos and documents through a vision model and get archival metadata back: a verbatim transcription of whatever is written on the front or back, a scene caption, keywords, and deliberately cautious date/location guesses - as JSON, NDJSON streams, or metadata written straight into the files with ExifTool.

Compatible with OpenAI, Anthropic, Gemini, and OpenRouter API keys.

Why should I use this?

I have inherited thousands of family photos and documents. I will never have time to review each one by hand, but an LLM first pass pulls the key data out of every scan and makes the eventual manual review far easier. This library automates that first pass.

Quick start for a single photo

You will need an LLM API key. This is separate from a chat subscription — API access is billed for what you use rather than a fixed monthly cost. Search "[provider] API key" and follow the provider's directions to set up billing and a key.

Install photokin and set up ExifTool:

pip install "photokin[openai]"          # or [anthropic] / [gemini] / [all]
export OPENAI_API_KEY=sk-...            # setx on Windows
python -m photokin.exiftool.fetch       # sets up ExifTool, on any OS

Two notes on the install lines:

• ExifTool is part of a normal install. It is how photokin reads the metadata your files already hold and how it writes results back into them — the whole archival workflow runs through it, so set it up unless you're embedding photokin in a tool that has its own metadata writer. The fetch command works on every OS: it downloads the official ExifTool release into ~/.photokin/bin, verified against the SHA256 that exiftool.org publishes, with no system install needed — and on macOS/Linux it skips the download when an ExifTool is already installed (brew install exiftool counts).

• photokin runs with the provider you installed. With exactly one provider SDK installed, it is used automatically — no flag needed. With more than one (say, [all]), pick per run with --provider anthropic, or set it once with the LLM_PROVIDER environment variable and never type it again — see Set your defaults once, which also covers setting a default model. OpenRouter is the one exception: it shares OpenAI's SDK, so it always takes an explicit --provider openrouter.

Now run your first analysis:

photokin scan_042.jpg --back scan_042-back.jpg

This calls the model but does not modify your photos: the result is one JSON document printed to your terminal — keyed by image path, one entry per file, so the back gets its own record. The one file it may touch is photokin's own keyword vocabulary (part of its install, not your pictures), where a newly proposed keyword can be added — --no-update-vocab turns that off. (To also save what each model call was built from — the request payloads, the assembled metadata, and a log, in a ./debug folder — add -v.) Abridged output:

{
  "results": {
    "scan_042.jpg": {
      "keywords": ["Postcard", "1940s", "Military personnel", "..."],
      "caption": "[Back]\n27 november 44\nAlthough, I personally did not see this cathedral...",
      "ai_caption": "[AI Analysis]: A printed postcard showing... Inferred date: 1944-11-27 (confidence 0.95; evidence: handwritten date on back).",
      "category": "Postcard",
      "location_guess": {"country": "France", "city": "Le Mans", "confidence": 0.9},
      "date_guess": {"iso": "1944-11-27", "confidence": 0.95, "pattern": "Y!M!D!"}
    },
    "scan_042-back.jpg": { "keywords": ["...", "back"], "...": "..." }
  },
  "errors": {}
}

The transcription (caption) and the interpretation (ai_caption) are kept strictly separate — the model is not allowed to "improve" what's actually written on the object. That separation is most of the reason this tool exists.

Happy with the result? Add -rw to the same command to also read the metadata the files already hold, analyze with that context, and write the results back into the files:

photokin scan_042.jpg --back scan_042-back.jpg -rw

-w modifies your image files — back them up before your first writing run. Exactly which fields land in which tags is listed in What gets written where; folder runs are covered in Folders and batches.

New to Python, or starting from a completely bare machine? See the full Windows Quick Start or macOS Quick Start walkthroughs below.

Windows Quick Start

This walks through a completely fresh Windows machine — nothing installed yet.

1. Install Python

Download Python 3.11 or newer from python.org/downloads. Photokin requires Python 3.11+.

On the first installer screen, check "Add python.exe to PATH" before clicking Install — this is the most common thing people miss, and without it python won't be recognized in a terminal.

Verify it worked by opening a new PowerShell window and running:

python --version

2. Create a project folder

Pick a folder to hold your virtual environment and any manifest/output files. This does not need to contain your actual photos — you'll point photokin at wherever those already live, by full path.

mkdir C:\Users\YourName\photokin-work
cd C:\Users\YourName\photokin-work

3. Create and activate a virtual environment

python -m venv .venv
.venv\Scripts\Activate.ps1

Your prompt should now start with (.venv).

Two common snags:

• Double-clicking Activate.ps1 in File Explorer opens it in a text editor instead of running it. This is expected — PowerShell scripts aren't meant to be launched by double-click. Always run it as a typed command from an open PowerShell window instead.
• "Running scripts is disabled on this system" error. PowerShell blocks script execution by default. Fix it once with:

  Set-ExecutionPolicy RemoteSigned -Scope CurrentUser
  

  Confirm with Y when prompted, then re-run the activation command. If you'd rather not change the execution policy, use Command Prompt instead of PowerShell and run .venv\Scripts\activate.bat.

4. Install photokin

Install with the extra for whichever provider you're using:

pip install "photokin[anthropic]"

(Swap anthropic for openai, gemini, or all as needed.)

5. Set your API key

For the current terminal session only:

$env:ANTHROPIC_API_KEY = "sk-ant-..."

To make it persist across future terminal sessions:

setx ANTHROPIC_API_KEY "sk-ant-..."

Note that setx doesn't affect your current window — open a new terminal to pick it up.

6. Set up ExifTool

ExifTool is what lets photokin read the metadata already in your files and write results back into them — the normal archival workflow needs it:

python -m photokin.exiftool.fetch

This downloads the official ExifTool binary into ~/.photokin/bin — no separate system install required.

Installing it does not turn writing on. Nothing is written to your files unless you add -w to a run, so the commands in step 7 still only read. See Reading and writing your files for what -w writes and where.

7. Run it

Give it the full path to the photo — you're in photokin-work, not in your pictures folder, and the type is detected from the path you pass:

photokin C:\Users\YourName\Pictures\scan_042.jpg --back C:\Users\YourName\Pictures\scan_042-back.jpg

or against a whole folder:

photokin C:\Users\YourName\Pictures\Scans\ > results.json

No --provider flag needed: you installed exactly one provider SDK in step 4, so photokin uses it. If you later install a second one, pick per run with --provider anthropic, or set it once with setx LLM_PROVIDER anthropic (new terminals pick it up) — see Set your defaults once.

These runs only print results. When the output looks right, the normal archival run is the same command plus -rw — read what the files already hold, write the results back — covered in Folders and batches.

Coming back later

Each new session, just reactivate the environment before running photokin:

cd C:\Users\YourName\photokin-work
.venv\Scripts\Activate.ps1
photokin ...

macOS Quick Start

This walks through a completely fresh Mac — nothing installed yet.

1. Install Python

Macs ship with an old system Python (and often no python command at all, only python3), so install a current one from python.org/downloads — Photokin requires Python 3.11+. If you already use Homebrew, brew install python@3.12 works just as well.

Verify it worked by opening a new Terminal window and running:

python3 --version

Use python3 (not python) for every command below — that's normal on macOS, not a sign something's wrong.

2. Create a project folder

Pick a folder to hold your virtual environment and any manifest/output files. This does not need to contain your actual photos — you'll point photokin at wherever those already live, by full path.

mkdir ~/photokin-work
cd ~/photokin-work

3. Create and activate a virtual environment

python3 -m venv .venv
source .venv/bin/activate

Your prompt should now start with (.venv).

One common snag: if python3 isn't found anywhere, macOS may prompt you to install the Xcode Command Line Tools (a separate, smaller download triggered the first time a python3/git/etc. command runs). Either let it install, or just use the python.org installer from step 1, which doesn't depend on it.

4. Install photokin

Install with the extra for whichever provider you're using:

pip install "photokin[anthropic]"

(Swap anthropic for openai, gemini, or all as needed.)

5. Set your API key

For the current terminal session only:

export ANTHROPIC_API_KEY="sk-ant-..."

To make it persist across future terminal sessions, add that line to your shell's startup file — ~/.zshrc on any Mac from the last several years (zsh is the default shell), or ~/.bash_profile if you're on bash:

echo 'export ANTHROPIC_API_KEY="sk-ant-..."' >> ~/.zshrc

Open a new terminal window (or run source ~/.zshrc) to pick it up.

6. Set up ExifTool

ExifTool is what lets photokin read the metadata already in your files and write results back into them — the normal archival workflow needs it:

python -m photokin.exiftool.fetch

The fetch command uses an ExifTool you already have when one is on your PATH; otherwise it downloads the official ExifTool distribution into ~/.photokin/bin, verified against the SHA256 that exiftool.org publishes, and runs it on the perl every Mac ships with. If you prefer a system install, brew install exiftool works just as well — run the fetch command afterwards and it will simply confirm the one it found.

Installing it does not turn writing on. Nothing is written to your files unless you add -w to a run, so the commands in step 7 still only read. See Reading and writing your files for what -w writes and where.

7. Run it

Give it the full path to the photo — you're in photokin-work, not in your pictures folder, and the type is detected from the path you pass:

photokin ~/Pictures/scan_042.jpg --back ~/Pictures/scan_042-back.jpg

or against a whole folder:

photokin ~/Pictures/Scans/ > results.json

No --provider flag needed: you installed exactly one provider SDK in step 4, so photokin uses it. If you later install a second one, pick per run with --provider anthropic, or set it once by adding export LLM_PROVIDER=anthropic to your ~/.zshrc — see Set your defaults once.

These runs only print results. When the output looks right, the normal archival run is the same command plus -rw — read what the files already hold, write the results back — covered in Folders and batches.

Coming back later

Each new session, just reactivate the environment before running photokin:

cd ~/photokin-work
source .venv/bin/activate
photokin ...

Folders and batches

The run you'll normally use is -rw:

photokin C:\Users\YourName\Pictures\Scans\ -rw
photokin box3_017.jpg --back box3_017-back.jpg -rw

Point photokin at a folder and it works through every image in it (non-recursively). By default:

• All scans of one physical object — a front and its back, a rescan and the original — are sent to the model together and analyzed as one unit.
• The results are combined into one coherent set of analysis fields shared across the group — if the front and the back both carry writing, the caption of both files includes both transcriptions. Two things stay per-file: the back/negative part keyword, and, for documents, each page's own caption (see the exception below).
• Grouping goes by file name only, following the naming conventions below. The model is never asked to guess which files belong together.
• A group with no front scan — only pages, only a negative, only a back — is analyzed like any other object.

Multipage documents are the one exception:

• A group of page-numbered files (letter-page1.jpg, letter-page2.jpg, ...) is still analyzed together, but each page's caption gets only that page's own transcription — it doesn't make sense to write a 63-page story into the metadata of all 63 files. This is not configurable; the closest lever is --group-by none, which analyzes every file alone.
• To get a full, readable transcript, add -s (short for --sidecar-md auto), which writes a Markdown transcript file beside each page when the model categorizes the object as a Document or Postcard — see A readable transcript beside each scan. It combines with the other short flags, so the archival run with transcripts is -rws.

A run without -w still calls the model but writes nothing back. photokin C:\Scans analyzes, prints the JSON to your terminal and touches nothing. Its plan summary ends with one extra row naming the next step:

[INFO] Plan for this run:
  input     : C:\Scans (folder, 12 file(s) in 5 group(s), group-by object)
  read      : none (-r not given)
  output    : stdout
  changeset : none (--changeset false)
  write     : none
  provider  : ChatGPT
  model     : gpt-4o
  note      : this run only prints results - your photos are not read or
              changed. For the normal archival run:
                  photokin "C:\Scans" -rw

The printed result has one entry per file — backs, variants, pages, negatives and crops included — with diagnostics and summaries going to stderr. To write results to a file instead of the terminal, see --output-file.

Naming conventions

Grouping is driven entirely by filename suffixes. The grammar is name[letter][-front|-back|-negative|-pageN][-crop], case-insensitive, applied right to left:

Example	Meaning
box3_025.jpg	the photo itself (the print's front, no variant letter)
box3_025-b.jpg or box3_025b.jpg	another scan of the same object (variant letter, with or without dash after a digit)
box3_025-back.jpg	the reverse side (-front and -negative work the same way)
album-page1.jpg, album-page2.jpg	ordered pages of one document
box3_025-back-crop.jpg	a cropped detail of its parent, recorded with the group but not analyzed as its own object while its parent is present — a crop with no parent fills the missing slot, and --group-by none analyzes every crop alone
box3_025.tif beside box3_025.jpg	the same scan in two formats — one object, not two photos

The variant letter comes before the part suffix (025b-back-crop.jpg), and a file with no explicit -pageN is only treated as page 1 if its group contains other numbered pages.

Every file also gets at most one keyword naming its part — back on a reverse side, negative on a negative, nothing on a front — so you can always tell which file is which afterwards. A back or Negative keyword you applied yourself is left exactly where it is.

Same name, different extension — one object, one call. A TIFF master beside the JPEG made from it is one scan of one print, so the pair claims one place in the group. The higher-fidelity file is sent to the model (TIFF first, then PNG, then the lossy formats) and the analysis is written to both — a folder of 200 TIFF/JPEG pairs uploads 200 images instead of 400. The run names each file it didn't upload and counts them in the closing N file(s) recorded without being sent to the model line; that number is the saving, not a warning. Images are also downscaled before upload to save tokens and bandwidth — tune that with --max-edge and --jpeg-quality (see Image handling).

Choosing how to group objects

--group-by is the one grouping axis:

• object (default) — every scan of one object is one group, and the whole group goes to the model in one call, so it can read detail off whichever scan came out clearest.
• pair — keeps a front with its back, but analyzes each rescan on its own.
• none — no grouping at all: every file is analyzed alone, and every crop becomes its own object.

Files that don't follow the naming conventions effectively run as --group-by none.

Reading and writing your files

ExifTool reads the metadata a file already holds (-r) and writes the analysis back into it (-w); the two combine as -rw.

What gets written where

Result field	Tag
ai_caption (the AI analysis)	EXIF:UserComment
caption (the verbatim transcription)	XMP-dc:Description
keywords	XMP-dc:Subject
title	XMP-dc:Title
date_guess (when confident enough)	EXIF:DateTimeOriginal
location_guess (when confident enough)	IPTC:Country-PrimaryLocationName / Province-State / City / Sub-location — not written by default: -r doesn't read these tags yet, so a location already in the file would be overwritten unread; opt in by naming them in --exiftool-fields — which replaces the whole list, so include the default tags you still want alongside them

Why read first

With -r, photokin reads EXIF:DateTimeOriginal, EXIF:UserComment, XMP:Description, XMP:Title and XMP:Subject before analysis, so a note, caption, title, date or keyword already living in an image rides along to the model as context. Two of those fields get special treatment:

• Dates. The file's own date is treated as evidence, not truth: on a flatbed scan DateTimeOriginal is the day you scanned the print, not the day the photograph was taken, so it never overwrites the model's date_guess — but it is what the date-correction heuristic compares that guess against before writing anything.
• Titles. Scanner software routinely writes "Scanned Image" or the bare filename into XMP:Title, so a title read out of a file does not beat the model. A title you supplied yourself, in a manifest or --meta, always wins.

A file -r asked for but could not read gets no proposed writes at all, with a warning naming it — unread is not empty, and writing against a before-snapshot that was never seen could overwrite metadata the file really holds. Fix whatever blocked the read (a locked or corrupt file) and re-run.

If a write fails

Files are written independently — a failure on one never touches its neighbors. To find out what happened and pick up again:

• The per-file reasons are logged as [ExifTool] Errors: before the run ends. Treat a listed file as unverified rather than untouched: ExifTool can write some of a file's tags and miss others in the same pass, so photokin counts nothing on that file as written — re-running it is the fix, not proof that something was lost.
• If writes were attempted and none succeeded, the run exits 2: some setting is wrong for every file (an unwritable --exiftool-fields tag, a read-only folder, a binary that will not run). Fix the setting and re-run. A run whose changeset simply proposed nothing to write exits 0.
• If only some files failed, the run exits 0: the settings were right, and one locked or corrupt file among many is ordinary. Fix those files and re-run the same command — captions merge instead of duplicating (see Captions), so already-written files come out unchanged. Note a re-run does call the model again for every group.

Manifest mode is the exception and always exits 0: the Lightroom plug-in reads per-item records, not exit codes.

Captions

For a group of scans of one object, photokin merges what you already wrote with what the model transcribed, and writes the same caption block to every file in the group.

The shape

Take a print scanned twice, plus the back of the second scan — box3_017.jpg, box3_017b.jpg, box3_017b-back.jpg. After a run, every one of the three files holds the same block:

[Photo A] Caption A
[Photo B] Caption B
[Back] Back of Photo B

Those files are one physical photograph, and which one you open a year from now is an accident of browsing — any of them should tell the object's whole story. The block is pure transcription: your captions plus the model's reading of what is written on the object, written to XMP-dc:Description. The model's interpretation of the scene (ai_caption) goes separately to EXIF:UserComment, never here.

Labels are only added when there is something to tell apart. A lone scan with no back — the overwhelmingly common case — keeps its caption exactly as you typed it, no brackets. One photo plus its back gets [Photo] / [Back]; lettered variants get [Photo A] / [Photo B], matching the letters on disk (a bare scan is variant A).

A caption you typed on one file will appear on its siblings. They are one object, so the front's "Ruth and Sam outside the bakery" ends up on the back scan too. If you don't want two files sharing a caption, they aren't one object as far as photokin is concerned — split the group, or run with --group-by none.

Your existing captions are kept

Nothing you wrote is ever deleted. A new transcription that differs from your caption is added beside it under its own label; one that matches it (ignoring punctuation, spacing, quoting and capitalization) is dropped as a duplicate. Anything that changes a word is kept — bakery, 1948 against bakery, 1949 is a different caption. If you reword a caption and want the old one gone, delete it yourself; photokin will not guess that a rewrite meant replace.

Running -rw repeatedly does not grow your captions: labelled lines are recognized as photokin's own and merged section by section, so after the first write the block is stable byte for byte. (A stray [AI Analysis] tail written into Description by an older release is recognized and stripped on the next read.)

Documents get their own page, not the whole book

Each page of a multipage document carries only its own transcription in XMP-dc:Description — you opened page 37 to read page 37, not the whole 63-page letter. Anything that is not an ordered sequence of pages (a front/back pair, a rescan, a variant) still gets the shared block above. An archive processed by an older photokin keeps the whole-document captions it already holds; re-running does not clear them.

A readable transcript beside each scan

The caption block lives inside XMP-dc:Description — readable with a metadata viewer, not by opening a file. --sidecar-md writes the same transcription as its own Markdown file beside each analyzed image, with frontmatter carrying that file's metadata (title, category, keywords, date, location, group, page number, and which model produced it):

• off (the default) — nothing new is written.
• auto — only for a group whose category comes back Document or Postcard. -s is shorthand for this one, and combines with the other short flags: photokin ./scans -rws is the archival run with transcripts.
• all — a sidecar for every emitted file, any category, except crops.

Whether a sidecar is written under auto is decided purely by the model's category verdict for the group — the page-numbered filenames play no part in it (they decide what each page's sidecar and caption contain). An explicit --sidecar-md off or all beside -s is refused as a contradiction, the same way -w and -v treat theirs.

photokin letter.jpg --sidecar-md all

That writes letter.md beside letter.jpg. The frontmatter's exact shape and chunked-document details are covered under Markdown transcript sidecars in Advanced usage.

Managing API keys

Keys are plain environment variables, one per provider. Photokin reads them when it builds the provider client and nowhere else. They never end up in results, changesets, or debug dumps.

Provider	Variable
OpenAI	OPENAI_API_KEY
Anthropic	ANTHROPIC_API_KEY
Gemini	GEMINI_API_KEY
OpenRouter	OPENROUTER_API_KEY

For the current terminal session:

export OPENAI_API_KEY=sk-...            # macOS / Linux
$env:OPENAI_API_KEY = "sk-..."          # Windows PowerShell

To make it stick across sessions, add the export line to your shell profile (~/.bashrc, ~/.zshrc), or on Windows run setx OPENAI_API_KEY sk-... once (takes effect in new terminals, not the current one). If you keep keys in a file, keep that file out of version control.

You only need the key for the provider you're actually using. It's worth setting a spend limit in your provider's dashboard.

Advanced usage

Everything below is opt-in/opt-out machinery for auditing, redirecting output, and bigger or more repeatable jobs. None of it is needed for the normal -rw run.

Previewing a run: --dry-run

--dry-run prints the plan summary — input, grouping, read set, write set, and the exact output and changeset paths the run would use — and stops before the first model call. Nothing is analyzed, nothing is written, nothing is spent. It is the way to check where a batch's writes and changesets would land before committing to it. Beside --generate-manifest, it reports the grouping that would be written and leaves the file alone.

Redirecting output: --output-file and sidecars

--output-file works for every input type — a folder, a manifest or one photo: a .ndjson path streams one record per finished photo (you can watch progress, and a crash doesn't lose completed work), while a .json path writes a single aggregate object atomically at the end. With it, stdout stays empty.

The changeset follows the output file: a changeset is otherwise written beside the input, so --changeset true on a photo folder drops the .ndjson inside that folder — pass --output-file a path in a folder you control and the changeset lands there instead.

--output-sidecars additionally writes a per-photo sidecar JSON next to each image (default off).

Every destination the run writes — --output-file, --generate-manifest, --log-file, the changeset — is checked against the run's inputs and its other destinations before being opened; a collision is refused (exit 2, naming both paths) rather than overwriting a file the run depends on. --dry-run runs the same check.

Changesets: an audit trail for writes

--changeset true emits a changeset NDJSON alongside the results: a record of proposed field writes that the ExifTool wrapper can apply to the files, either in the same run (-w, or --exiftool-write true --exiftool-fields EXIF:UserComment) or later and separately. It is written to dirname(--output-file or input) as <stem>_changeset.ndjson — so --output-file results.ndjson yields results_changeset.ndjson, and photokin ./scans/ --changeset true yields scans_changeset.ndjson inside the folder.

Since the changeset is a plain record of proposed writes, you can inspect it first and apply it separately:

python -m photokin.exiftool --changeset results_changeset.ndjson --enabled --dry-run   # counts what would be written
python -m photokin.exiftool --changeset results_changeset.ndjson --enabled            # actually writes

The standalone applier also takes --fields to narrow which tags may be written, --write-sidecar-only to write .xmp sidecars instead of touching the originals, --no-overwrite-original to keep ExifTool's _original backup files, and --output summary.json for a machine-readable result. Date tags (EXIF:DateTimeOriginal, EXIF:CreateDate) are normalized to EXIF's YYYY:MM:DD HH:MM:SS format on the way in; unparseable dates become warnings, not writes.

Manifest mode

A manifest is a JSON file listing exactly what to process — an items array where each entry needs only a path. It is mainly how another program drives photokin (the Lightroom plug-in works this way; see Integrating photokin as a subprocess), and it also makes a big job repeatable and editable. --generate-manifest turns a folder into exactly that file:

photokin ./scans/ --generate-manifest scans-manifest.json

It writes the manifest the folder run would have used — same files, same order — and exits without calling the model, so it costs nothing and doubles as a way to check the grouping before committing to a batch. Edit it (add is_back, group, existing metadata) and feed it straight back: photokin scans-manifest.json.

The sample below declares one physical object, a front scan and its back, and one line of batch-wide background context. Note the underscore in box3_017_back.jpg: the filename grammar reads only the hyphenated -back, so it is the is_back flag that folds the two files into one group and one model call rather than two unrelated photos.

batch.json:

{
  "items": [
    {"path": "scans/box3_017.jpg"},
    {"path": "scans/box3_017_back.jpg", "is_back": true}
  ],
  "photo_context_text": "Church family photos, mostly New Jersey, 1930s-1950s."
}

photokin batch.json --output-file results.ndjson --changeset true

Photo flags

Flags are optional when the filename already says the same thing; they exist so files that don't follow the naming conventions can still be grouped correctly. An explicit flag always beats the filename, in both directions and including when the two contradict each other — anything else would leave the flag inert in exactly the situation it is there for. Every override that changes what the filename implied is logged, so a typo is visible rather than silent.

Key	Effect
is_back	true marks the reverse side, false marks the front. true also repairs the group key by stripping a trailing back token, which is what puts box3_017_back.jpg in the same group as box3_017.jpg.
is_crop	true marks a cropped derivative, so the file is recorded with its group but not analyzed; false unmarks a file whose name ends in -crop.
version	The variant id, replacing any letter read off the filename. Any string, not just one letter; empty means no variant.
group	The group key outright, for names the grammar cannot parse at all. base_id is accepted as an alias and loses to group when both are given.
preferred	Breaks a tie between two files claiming the same slot — the same side of the same variant — so the one you name is the one sent and the other is recorded and warned about. It chooses between candidates; it cannot create a place for one. See below.

is_back and is_crop may be written as JSON true/false, as 0/1, or as the strings "true", "false", "yes", "no". A null value means "not specified" and leaves the filename in charge.

preferred is the exception and does not read that grammar: it is plain truthiness, so any non-empty string sets it and "preferred": "false" means true. Write it as a JSON true, or leave the key out entirely. It also nominates the file the group's analysis is filed under.

preferred chooses between candidates for a slot; it cannot create one. A crop always yields to its listed parent, and a file with no part left to claim (a plain album.jpg beside an explicit album-page1.jpg) cannot be promoted into one. Both cases log a warning naming the file and are listed in the result record under all_variant_files.crops / all_variant_files.displaced, so nothing disappears quietly.

Replaying a manifest. A manifest run with -r also records what ExifTool read into the output document, so replaying that manifest later (photokin scans-manifest.json) needs no ExifTool at all. Replay with -r to reproduce the original result exactly.

Markdown transcript sidecars for documents

--sidecar-md {off,auto,all} (default off) writes <stem>.md beside each analyzed image — the same path derivation --output-sidecars uses for <stem>.json, and the same failure contract: an unwritable destination logs a warning and does not take the analysis down with it.

auto gates on the group's own category result — only Document and Postcard trigger it, the two categories that are mostly text; Photo Page (an album page with mounted photos and typed captions) deliberately does not. all ignores category and writes for every emitted file.

Crops never get a sidecar — a crop isn't analyzed on its own, so its sidecar would only duplicate its parent's.

Frontmatter carries the same values the changeset would write for that file, plus the structural facts that place it in its group: group id, part label, page number, page count, and every filename in the group. A worked example, page 2 of a six-page letter:

---
source_file: "box3_017-page2.jpg"
group: "box3_017"
part: "Page 2"
page: 2
page_count: 6
group_files: ["box3_017-page1.jpg", "box3_017-page2.jpg", "box3_017-page3.jpg", "box3_017-page4.jpg", "box3_017-page5.jpg", "box3_017-page6.jpg"]
title: "Letter from Ruth, November 1944"
category: "Document"
keywords: ["Document", "Ruth", "Le Mans", "1944"]
date: "1944-11-27"
date_pattern: "Y!M!D!"
date_confidence: 0.95
location: {country: "France", city: "Le Mans", confidence: 0.9}
analyzed_by: "Claude claude-sonnet-4-6 (2026-08-27)"
---

# Letter from Ruth, November 1944

[AI Analysis]: A handwritten letter, three pages, in a woman's hand...

## Transcription — Page 2

Dear Mother,

We arrived in Le Mans yesterday, tired but glad to be off the train at last.

A key with nothing to say is omitted — a file with no location guess writes no location key. When a chunked document's consolidation pass (see below) corrects a page number, page carries the corrected value and the filename's own number is kept alongside as page_from_filename. When nothing can be attributed to this file specifically, the body falls back to the whole group's caption block and the frontmatter marks it transcription_scope: group.

A sidecar is derived output, the same as the JSON one --output-sidecars writes: a re-run overwrites it outright rather than merging with what's already there, unlike the caption block written into the image itself, which is merged section by section (see Captions).

Large documents: --max-images-per-call

One model call ordinarily carries a whole group, however large — a 63-page memoir would be one call holding 63 images. --max-images-per-call N (default 8) splits an oversized group into several calls. It never splits mid-page, a page's own rescans never straddle a block, and a front, back and negative always ride together in the first call. After the last chunk, one further text-only call consolidates the chunks' provisional keywords/title/category/date/location into the group's one final answer. It does not re-transcribe anything — the per-chunk transcriptions stand as written.

A group at or under the cap is entirely unaffected, and --max-images-per-call 0 disables chunking outright. Chunking sends the same number of images either way; it adds the repeated prompt on every chunk call plus the consolidation call's tokens, and buys per-page attention that doesn't thin out on long documents, payloads under provider size ceilings, and failures that name which chunk failed.

The consolidation pass's page-order verdict is recorded, never acted on: when the pages read out of filename order, the corrected page number goes into the record and the sidecar's page field with a warning naming the group, but no file is renamed or renumbered — that stays a decision for a person.

All flags

Input modes

One input, given positionally; its type comes off the path. A directory is a folder, a .json file is a manifest, an image file is a single photo — and the run says which it decided on before it does anything else, so a mis-detection is visible rather than surprising. The two aliases are still accepted and assert the type instead of detecting it; passing a positional and an alias is an error.

Flag	What it does
INPUT (positional)	Folder of scans, .json manifest, or a single image; the type is detected from the path
--back PATH	Back-side image, for single-photo input only
--meta PATH	Original metadata JSON, for single-photo input only
--folder DIR	Alias for a folder INPUT; asserts the path is a directory
--manifest PATH	Alias for a manifest INPUT; asserts the path is a .json manifest file

Provider and model

Flag	What it does
--provider {openai,anthropic,gemini,openrouter}	Which backend to call. Default: LLM_PROVIDER if set, else the one provider whose SDK is installed; with several installed the choice is required. See Providers
--openai-model NAME	OpenAI model (default gpt-4o)
--claude-model NAME	Claude model alias (sonnet or haiku); resolves to a current model id (default sonnet)
--gemini-model NAME	Gemini model (default gemini-2.5-flash)
--openrouter-model SLUG	Any vision-capable OpenRouter slug (default moonshotai/kimi-k3)

Image handling

Flag	What it does
--max-edge N	Downscale the longest edge before upload; 0 keeps original size. Smaller is cheaper, larger reads fine print better (default 1024)
--jpeg-quality N	JPEG quality 1-100 for the uploaded copy (default 80)

Context

If you are processing a large number of photos related to a single event, you can add context around that event that will be shipped with the LLM call. For example if the whole photo set is part of a wedding. The context could include dates, locations, people to help make the LLMs job easier.

Flag	What it does
--photo-context-text TEXT	Inline background context, treated as authoritative
--photo-context-file PATH	Same, from a UTF-8 text file

Grouping and apply behavior

Flag	What it does
--group-by {object,pair,none}	Grouping granularity, the one axis (default object). object: every scan of one print is one object and shares a single analysis. pair: each rescan — print plus variant letter — is analyzed on its own. none: every file alone. See below
--date-confidence-threshold X	Minimum model confidence before a date guess is written into a file that has no date, 0-1 (default 0.6). Replacing a date the file already holds is governed separately and costs more; see below
--location-confidence-threshold X	Same, for location guesses (default 0.7)
--no-update-vocab	Don't append newly proposed keywords to the vocabulary file

Output

Flag	What it does
--output-file PATH	.ndjson streams one record per finished photo; .json writes one aggregate object atomically. Works for every input type; without it, results go to stdout
--pretty-json {true,false}	Indent the stdout result document (and an aggregate .json --output-file) for human reading (default true). Pass false for compact single-line output, e.g. when a script parses stdout itself rather than reading it with a JSON library
--output-sidecars	Also write a per-photo sidecar JSON next to each image (default off)
--sidecar-md {off,auto,all}	Also write a per-part Markdown transcript sidecar next to each image. off: nothing (default). all: every emitted file except crops. auto: only for a group whose category is Document or Postcard
-s	Shorthand for --sidecar-md auto; combines with the other short flags as -rws. A --sidecar-md value that contradicts it is an error rather than a guess, and like -w and -v it is refused beside --generate-manifest, which makes no model call
--max-images-per-call N	Cap on images sent in one model call. A group whose payload exceeds it is split into contiguous chunks (a front/back pair is never split across chunks) plus one text-only consolidation call that merges the chunks' metadata and corrects page order; a group at or under it is unaffected (default 8, 0 disables chunking)
--generate-manifest PATH	Write the manifest folder or single-photo input would be grouped into, then exit without calling the model (not valid with manifest input)
--batch-id ID	Identifier added to each record on the .ndjson streaming path, and used to name debug-dump files. It does not appear in the aggregate .json or on stdout
--changeset {true,false}	Emit a changeset NDJSON of proposed file writes, for every input type (default false)
--dry-run	Print the plan summary and stop, before the first model call. Nothing is analyzed and no destination is touched. Beside --generate-manifest, reports the grouping it would write and leaves the file alone

sidecar-xmp and sidecar-json are reserved spellings in this same family (not yet flags photokin accepts) — XMP for standard metadata sidecars when they arrive, JSON for the day --output-sidecars is folded in as an alias of sidecar-json all — the way -R is reserved below, and must not be spent on anything else.

ExifTool read and write-back

Flag	What it does
-r, --read	Before analysis, read EXIF:DateTimeOriginal, EXIF:UserComment, XMP:Description, XMP:Title and XMP:Subject out of the files and send them to the model, for every input type. Only fills what the input does not already carry; nothing is written. Mirrors -w
-w, --write	Shorthand for --changeset true --exiftool-write true: record the proposed writes and apply them. An explicit flag that contradicts it is an error rather than a guess
--exiftool-write {true,false}	Apply changeset fields to the files after analysis (default false; nothing is written without an explicit opt-in)
--exiftool-fields TAGS	Comma-separated tags ExifTool may write. The default is every tag in the What gets written where table except the location tags — those are an explicit opt-in until -r learns to read them, so a curated location is never overwritten unread. The flag replaces the default list rather than adding to it, so name every tag you want written. A launcher that writes some tags itself (the Lightroom plug-in writes the XMP tags through the catalog SDK) should narrow this explicitly, e.g. --exiftool-fields EXIF:UserComment
--exiftool-path PATH	ExifTool binary to use (default: auto-detect)

-r is the read half and -w the write half; the short letters are deliberately symmetrical, and they combine as -rw (or -wr) exactly like any other pair of short flags — that combined form is the one to reach for, for the reason given above. -R is reserved for the recursive-folder flag that is still deferred (it changes grouping semantics across directories and interacts with write safety, so it gets its own change), and must not be spent on anything else.

Rename mode [BETA FEATURE]

See Rename mode: --rename below for what it does. --rename is a mode flag: like --generate-manifest, it stops the run before any model call, and it takes a folder or manifest input — not a single photo.

Flag	What it does
--rename PREFIX	Plan a grammar-aware mass rename of the input folder or manifest's files under PREFIX; print the preview and stop. -w applies it. --exiftool-write and --output-file are refused beside it — rename mode writes no tags, and --plan-out is its own destination
--digits N	Zero-padded number width (default 3)
--order {name,natural}	Fallback ordering when no item carries an explicit manifest order (default name). natural compares digit runs numerically, so file9 precedes file10
--undated LITERAL	Stand in for {date} in a group with no date, instead of refusing to plan it; those groups form their own numbering bucket
--today YYYY-MM-DD	Override {today} (default: the run's own date), so a batch scanned earlier can carry its own date and a plan stays reproducible
--companions EXT[,EXT]	Extra non-image extensions carried along with a renamed image, beyond the default .md, .json, .xmp, .txt
--plan-out PATH	Write the plan as JSON to PATH (see docs/rename-contract.md), instead of — or beside — the preview table
--rename-undo [JOURNAL]	Reverse the latest applied rename in the positional folder, or the named journal file
--rename-resume [JOURNAL]	Finish an interrupted rename run in the positional folder, or the named journal file, forward
--rename-finish PLAN	Rename only the companions of a --rename plan whose images a catalog application has already renamed

Debug

Flag	What it does
--debug-dump-llm-request {true,false}	Save full request payloads to disk before each model call (default false)
--debug-dump-dir DIR	Where those dumps go. Default depends on the input: <dirname of --output-file, else of the manifest>/debug for manifest input, and ./debug under the working directory for folder and single-photo input

Providers

OpenAI, Anthropic, Gemini, and OpenRouter (any vision-capable slug — Kimi, Grok, Qwen, ...). Only the SDK for the provider you use needs to be installed, and only that provider's key needs to be set.

Which provider a run uses is decided in this order: the --provider flag, else the LLM_PROVIDER environment variable, else the provider whose SDK is installed. With exactly one SDK installed there is nothing to say — installing photokin[anthropic] was already the choice. With several installed (or none) and nothing chosen, the run stops with exit 2 before spending anything, and the error says how to choose. OpenRouter is the one provider never picked automatically: it speaks the OpenAI-compatible API through the openai SDK, so install the [openai] extra, set OPENROUTER_API_KEY, and select it explicitly.

Set your defaults once

The provider and each provider's model have an environment variable behind the flag, so a machine that always uses the same setup never types either:

Setting	Flag (per run)	Env var (set once)	Default
Provider	--provider	LLM_PROVIDER	the one installed SDK
OpenAI model	--openai-model	OPENAI_MODEL	gpt-4o
Claude model	--claude-model	CLAUDE_MODEL	sonnet
Gemini model	--gemini-model	GEMINI_MODEL	gemini-2.5-flash
OpenRouter model	--openrouter-model	OPENROUTER_MODEL	moonshotai/kimi-k3

Flags beat env vars, which beat the defaults. The whole set-and-forget setup is the API key plus these two variables. On Windows (new terminals pick them up):

setx ANTHROPIC_API_KEY "sk-ant-..."
setx LLM_PROVIDER anthropic
setx CLAUDE_MODEL haiku          # optional - sonnet is the default

On macOS/Linux, the same three as export lines in ~/.zshrc or ~/.bashrc:

export ANTHROPIC_API_KEY="sk-ant-..."
export LLM_PROVIDER=anthropic
export CLAUDE_MODEL=haiku        # optional - sonnet is the default

After that, photokin ./scans/ -rw is the entire command, every time. (CLAUDE_MODEL also accepts a full claude-* model id, not just the sonnet/haiku aliases — useful for a model newer than photokin's pins.)

Providers retire and rename models over time — OpenRouter slugs especially come and go. When that happens to the model a run asked for (or to photokin's own pinned default), the run stops on the first model call with a model_not_found error naming the flag and env var to pick a current one, rather than failing every photo in the batch the same way.

Layout

Layer	Where	What it does
Core library	photokin/	Prompts, provider dispatch, JSON parsing/repair, metadata merge, changeset emission. No ExifTool dependency.
ExifTool wrapper	photokin/exiftool/	Hydration (read before analysis) and apply (write after).

Dependency direction: the wrapper imports from the core; the core never imports the wrapper. The CLI (photokin/cli.py) composes them into the full pipeline: hydrate, analyze, apply. Embedders who don't want ExifTool can call the core directly — core.process_manifest_stream takes any metadata_hydrator callable, or none.

Tests

From the repository root:

python -m pytest

Runs photokin/tests/ and tests/, which pyproject.toml sets as the test paths. Python 3.11+.

Integrating photokin as a subprocess

This section is for a plugin or script that launches photokin (or python -m photokin.cli) as a subprocess, cannot read a return value, and often cannot even read stderr — the Lightroom plugin this was built for launches fire-and-forget (start /B on Windows, output discarded) and learns what happened only from the files photokin wrote. Everything here exists to make that mode of use safe and observable.

The problem this solves

Without what follows, a launcher watching only --output-file has one signal: did the file appear, and does it have as many lines as the manifest has items. That answers "it worked" but not "it is still running" versus "it already failed" versus "it will never appear" — an unknown flag, a bad manifest, a missing provider key, and a dead ExifTool binary all look identical: no file, forever. The pieces below close that gap.

The run envelope

Whenever --output-file names a .ndjson destination, the file carries run: ... records interleaved with the normal per-file path/status records — the same file, not a second one, so a caller tailing it sees everything in one stream:

run value	When	Carries
start	As early as the destination is known — before almost every pre-flight check, including ones that used to leave no trace at all (an unknown flag, an unwritable ExifTool tag, a missing or ambiguous provider, a missing ExifTool binary, a malformed manifest)	Nothing beyond the envelope fields below
plan	Once every pre-flight check has passed, right after the plan summary is logged	plan: the same fields as the stderr plan summary, as a dict (input_kind, file_count, provider, model, ... — see RunPlan in cli_messages.py)
progress	Once per group, right before it starts	group, index, of — a liveness signal for a group whose single model call may run for minutes with nothing else on the stream to show it hasn't died
exiftool_apply	After -w applies the changeset, if one was written	summary: files seen/written, tags written, errors, warnings
complete	The run finished (whether or not every group succeeded — "every group failed" is not a fatal error in manifest mode; see When calls fail)	files_recorded, groups_failed, files_unsent
cancelled	The run stopped early via --cancel-file (below)	Same three fields, counting only what completed before the stop
fatal	Any refusal or unrecoverable error, at any point after start	error: {"type": ..., "message": ...}

A run always ends with exactly one of complete, cancelled, or fatal — a caller can wait for any of the three as the definitive "done" signal, rather than inferring completion from the line count, which breaks the moment per-file emission ever changes shape (this happened once already, before the envelope existed).

Two destinations are deliberately exempt. --dry-run never opens the envelope — that flag's whole point is that nothing is touched, and the envelope is a destination like any other. --generate-manifest beside --output-file is refused outright before either can be written (see All flags), so there is never a results file for it to open.

One safety property carries over unchanged: a pre-existing --output-file is left completely untouched by a refusal. The envelope opens immediately only for a destination that does not exist yet; for one that does, it opens only once every check has passed and the run is committing to overwrite it anyway — at that point it gets the same start/plan records a fresh destination got immediately.

Every record — envelope and per-file alike — carries schema_version (currently 3) and, when --batch-id was given, batch_id. schema_version bumps whenever a record's shape changes in a way a consumer could care about; see --capabilities below for a caller that wants to check compatibility rather than discover it the hard way, the way photokin/README.md's ## Providers section describes an older mismatch doing.

Per-file error payloads also carry two optional fields beyond the type/message documented under When calls fail: provider_message (the provider's own error text, extracted from the SDK's structured response rather than read off a Python exception's str(), which for these SDKs is often the whole body rendered as a dict repr) and retry_after (seconds, when the provider's response included one — reliably available for OpenAI and Anthropic, not for Gemini).

Cancelling a run in progress: --cancel-file PATH

Photokin polls for this path once before each group starts (never mid-group — a group is one model call under the default object grouping, so there is no narrower point to check). Once the file exists, the run stops cleanly: whatever completed is kept, -w's ExifTool apply still runs over it, the envelope closes with run: cancelled instead of run: complete, and the process exits 0. Nothing is spent on groups that hadn't started yet.

photokin batch.json -rw --output-file results.ndjson --cancel-file results.ndjson.CANCEL
# from another process, at any point:
touch results.ndjson.CANCEL   # or: New-Item on Windows

Debugging a run: -v and its parts

-v / --verbose bundles three things — the same relationship -w has to --changeset/--exiftool-write — so a caller that wants everything a run could leave behind for debugging asks for it with one flag instead of three:

Flag	On its own	Under -v
--debug-dump-llm-request {true,false}	Write the full provider request payload (assembled prompt, images) to disk before each model call	true
--debug-dump-hydration {true,false}	Write each group's assembled metadata to disk before it is merged into a prompt — what -r read plus whatever the manifest supplied, one step upstream of the request dump	true
--log-file PATH	Duplicate the run's log output into this file, in addition to stderr	Defaults to <debug-dump-dir>/<batch-id or "run">.log if not given explicitly

All three dumps land in --debug-dump-dir (default ./debug, or <manifest/output-dir>/debug for manifest input), one folder per run holding everything: the LLM requests, the pre-prompt metadata, and now the log. An explicit value for any of the three individual flags always wins over what -v would otherwise set, and an explicit value that contradicts -v (-v --debug-dump-hydration false) is refused rather than silently picked between, the same as -w beside an explicit --changeset false. Like the write bundle, none of the three do anything useful without a model call, so all three are refused beside --generate-manifest — except a truly explicit --log-file, which still attaches, since even a --generate-manifest run has something worth logging.

Checking compatibility: --capabilities

photokin --capabilities

Prints this build's contract as JSON and exits, before any input is required — the same way asking for help does:

{
  "version": "0.6.2",
  "ndjson_schema_version": 3,
  "changeset_schema_version": 2,
  "canonical_tags": {
    "ai_caption": "EXIF:UserComment",
    "caption": "XMP-dc:Description",
    "keywords": "XMP-dc:Subject",
    "title": "XMP-dc:Title",
    "date_guess": "EXIF:DateTimeOriginal",
    "location_guess": {"country": "IPTC:Country-PrimaryLocationName", "state": "IPTC:Province-State", "city": "IPTC:City", "sublocation": "IPTC:Sub-location"}
  },
  "providers": ["openai", "anthropic", "gemini", "openrouter"],
  "flags": ["--back", "--batch-id", "..."]
}

Meant to replace an install-time probe (importing some internal symbol and trusting a pip version pin to mean everything else still matches) with a real, versioned answer a launcher can gate a run on instead of discovering a mismatch mid-batch. canonical_tags in particular is worth checking before a batch: an earlier photokin release wrote the wrong ExifTool tag spelling entirely (XMP:dc:Description instead of the writable XMP-dc:Description), which silently dropped every caption it tried to write rather than failing — a --capabilities check catches that class of mismatch instead of losing data quietly. flags is read live off the argument parser, so it can never drift from what the installed build actually accepts.

Checking your current settings: --show-config

photokin --show-config --provider openai --jpeg-quality 90

Prints this invocation's fully resolved settings as JSON and exits, before any input is required — the same timing as --capabilities, but a different question: not "what can this build do" but "what will this exact command line actually use" once every flag, environment variable (OPENAI_MODEL, LLM_PROVIDER, EXIFTOOL_FIELDS, ...) and built-in default has been resolved down to one value:

{
  "provider": {
    "selected": "openai",
    "installed_sdks": ["openai", "anthropic"],
    "api_keys": {
      "openai": {"env_var": "OPENAI_API_KEY", "set": true},
      "anthropic": {"env_var": "ANTHROPIC_API_KEY", "set": false},
      "gemini": {"env_var": "GEMINI_API_KEY", "set": false},
      "openrouter": {"env_var": "OPENROUTER_API_KEY", "set": false}
    }
  },
  "models": {"openai": "gpt-4o", "anthropic": "sonnet", "gemini": "gemini-2.5-flash", "openrouter": "moonshotai/kimi-k3"},
  "image": {"jpeg_quality": 90, "max_edge": 1024},
  "grouping": {"group_by": "object", "max_images_per_call": 8},
  "confidence_thresholds": {"date": 0.6, "location": 0.7},
  "sidecar_md": "off",
  "update_vocab": true,
  "changeset_requested": false,
  "exiftool": {
    "write_enabled": false,
    "fields": ["EXIF:UserComment", "..."],
    "configured_path": null,
    "resolved_path": "C:\\...\\exiftool.exe",
    "resolved_error": null
  }
}

Each provider's API key is reported as set/not only — the value itself is never read into the output, so this is safe to paste into a bug report. provider.selected is null when nothing resolves it (no --provider, no LLM_PROVIDER, and zero or several SDKs installed) — the same ambiguity a real run would refuse over, printed here to stderr as it is refused rather than left unexplained. exiftool.resolved_path/resolved_error report whether the ExifTool binary photokin would actually call is findable right now, the same lookup -r/-w depend on, without needing a real file to run it against.

A clean refusal for a headless launcher: empty or malformed argv

Running photokin with no arguments at all normally prompts on stdin — a courtesy for a human at a keyboard. A subprocess launcher has no keyboard, so photokin checks sys.stdin.isatty() first: with no terminal attached, an empty argument list is a usage error (exit 2) instead of a stdin read that would just hang. Separately, an argument list argparse cannot parse at all (an unknown flag, most often the result of a quoting bug upstream) still exits 2 with nothing on --output-file to read — argparse rejects the whole invocation before this module ever learns what the destination was meant to be — but a best-effort scan for --output-file in the raw arguments means even this earliest failure usually still lands a run: start + run: fatal pair in the results file, rather than leaving no trace anywhere a launcher can see.

BETA FEATURE: Rename mode: --rename

--rename PREFIX cleans up and renumbers a folder's files under a prefix you choose, keeping every variant tag the naming grammar above already understands and closing the gaps in the numbering. It reads the folder's current order, the same (name.lower(), name) order every other mode uses:

file102.tif          ->  newname-001.tif
file105.tif          ->  newname-002.tif
file105b.tif         ->  newname-002b.tif
file105b-back.tif    ->  newname-002b-back.tif

That is the whole feature: "clean up and rename the files in this folder using this prefix." A - always separates the prefix from the number, so parse_media_filename reads a renamed file back exactly the way it read the original.

Preview, then -w, exactly like the normal run. photokin ./scans --rename "newname" alone plans the rename, prints the preview, and touches nothing — the same "check it's wired up" shape as a bare analysis run. Nothing is renamed until you add -w:

photokin ./scans --rename "newname"                       preview, touches nothing
photokin ./scans --rename "newname" -w                    record the plan and apply it

The prefix can be a template, not just a literal string — {date}, {today}, {folder} and {orig} tokens, each with an optional :FORMAT on the two date ones:

photokin ./scans --rename "{date:yymmdd}-bag" -w          520601-bag-001.tif; numbering restarts per date
photokin ./scans --rename "{today:yymmdd}-bag" -w         batch date (the run date) instead of each photo's own
photokin ./scans --rename "newname{date:yyyy-mm-dd}" -w   newname1952-06-01-001.tif
photokin ./scans --rename "{orig}" -w                     keep the current prefix, just renumber and clean up

A prefix that renders differently per file (any template using {date}) starts its numbering over at 1 for each distinct rendered value, so a folder spanning several scanning sessions gets one clean sequence per session rather than one long one. Companions sharing an image's stem (.md, .json, .xmp, .txt, plus a .jpg twin of a .tif) are carried along automatically; --companions EXT[,EXT] adds more extensions to that set.

Undo. Every apply writes a journal beside the renamed files before it renames anything, so photokin ./scans --rename-undo reverses the most recent applied run in that folder — or pass a journal path directly for an older one. An interrupted run resumes forward with --rename-resume instead of undoing; both read the journal back rather than re-planning. An undo that can only reverse part of a run leaves its journal open and says what is left, so running it again picks up the remainder rather than refusing as already undone. A journal path that is only a symlink is resolved before it is read, so the undo (or resume) acts on the folder its records actually describe — the linked-to journal's own folder — never on the folder holding the link.

No destination doubles as a source. --plan-out and the changeset -w writes are checked against everything else the run touches — every photo and companion it would rename, a file it reports left behind, an earlier run's journal in that folder, the manifest it read, and the names it is about to rename onto — and refused (exit 2, naming both the destination and what it turned out to be) rather than silently overwritten. That check runs as part of planning, before the plan file or the changeset is opened, so it applies to a bare preview exactly as it does under -w, and under --dry-run too.

Photokin renames files on disk only with -w. A folder tracked by a catalog application (Lightroom and the like) must be renamed through that application, not through photokin directly — photokin cannot tell such a folder apart from an ordinary one on its own, so every --rename preview says so. When a manifest was exported by that application (it carries managed_by), -w becomes a usage error rather than a guess: photokin plans the rename and, with --plan-out PATH, writes it out for the application to apply.

See docs/rename-mode.md for the full specification and docs/rename-contract.md for the manifest, plan and changeset shapes a wrapper reads.