Skip to main content

Kibsu

CI CodeQL OpenSSF Scorecard PyPI Python 3.8+ License: MIT Dependencies: none OS

What can your agents not do in this repository yet?

You have written instructions for coding agents — AGENTS.md, CLAUDE.md, a skills/ directory, .cursorrules. Kibsu reads them alongside your git history and reports which of those instructions anyone could actually verify were followed, and which ones only work when a human remembers.

The read-only commands write nothing — run one, then run git status. Four commands write on purpose and say so before they do: index (the index file), install and gate --install (vendored tools plus hook wiring, reversible), check --receipt (a receipt file). Everything else — report, explain, audit, discover, survey, guide, learn, tokens — reads only.


Run it

No dependencies. Python 3.8+.

pip install kibsu
python -m kibsu report /path/to/any/repo

Or try it without installing anything into your environment: uvx kibsu report /path/to/any/repo (pipx run kibsu report ... is the same idea). kibsu ... and python -m kibsu ... are the same program; this page writes the long form because it is the one that also works from a bare clone, with no install at all. One honesty note: the short kibsu command ships from 0.9.0 — through 0.8.0 the package declared no command, and uvx kibsu answered "does not provide any executables" (see CORRECTIONS.md, 2026-10-10).

report is one of thirteen subcommands — python -m kibsu --help lists them all. It is the one to start with, and the only one you need to read this page.

Real output, against a public repository at commit 3dcbd5c:

  WHAT YOUR AGENTS CANNOT DO HERE YET
  /tmp/superpowers
  --------------------------------------------------------------------------
  x  Find your docs             89 markdown files, no index. An agent must grep the tree.
  +  Know your conventions      consistent frontmatter (description, name) - enforceable.
  +  Prove they followed        13.1% of your procedural instructions are verifiable (above the 7.6% public median).
  x  Resume after a break       1 of 1 artifacts your instructions promise have never existed in any commit.
  ?  Follow your own rules      COULD NOT CHECK - no index file to check history against (looked for docs/index.json, .kibsu/index.json, docs/index.json).
  --------------------------------------------------------------------------
  2 of 5 ready.  1 could NOT be checked - that is not a pass.
  Nothing was written to this repo - run `git status` to confirm.

That block was last re-run against 3dcbd5c on 2026-10-11, with scorer 0.11.0 — the fifth re-paste it has needed, each one recorded. One figure moved this time: the median it is compared against, 7.5% to 7.6%, when the survey was re-measured in sentences instead of lines (see CORRECTIONS.md, 2026-10-11). The repository's own 13.1% did not move, though what stands under it did: 46 of 352 sentences in 9 procedure units, where the line count had 50 of 381 in 10. The re-paste before it (2026-10-10, scorer 0.10.0) moved one line, and both numbers on it were stale for different reasons. 15.6% became 13.1%: the block had not been re-run since scorer 0.6.0, while the survey table further down was re-measured three times — so this page showed two different figures for the same repository at the same commit. And 9.4% became 7.5%: that one was stale inside the tool. report carries the survey median as a constant, and it sat at the scorer-0.6.0 value through three releases while the scorer and this page's own table moved on (see CORRECTIONS.md, 2026-10-10 — a test now fails while the constant and evidence/ disagree). Both runs were on Windows; every other line matched the earlier Linux paste except for path separators, so those lines are kept as pasted. The three earlier re-pastes (Title-case directives under scorer 0.6.0, the scaffold-scope change under 0.5.0, the pre-?-mark build before that) are narrated in this file's git history. A pasted sample a reader could reproduce and get something else from is the same reproducibility defect as the SHA-less survey table further down, and it is recorded rather than quietly corrected for the same reason.

Reproduce it:

git clone https://github.com/obra/superpowers /tmp/superpowers && cd /tmp/superpowers && git checkout 3dcbd5c
python -m kibsu report /tmp/superpowers
git -C /tmp/superpowers status --porcelain

The last command prints nothing. That is the point.

(report exits 3 here, not 0 — two questions came back not-ready and one could not be checked, which is the finding, not a failure to run. The commands are deliberately not chained on && for that reason: && would swallow the git status proof in exactly the case worth proving.)

+ ready · x not ready · ! not applicable here · ? could not be checked

A check that could not run gets its own line and its own mark, and the summary says so out loud. Printing one line fewer would make "2 of 4" and "2 of 5" indistinguishable, and the check that cannot run is reliably the uncomfortable one.

See a repo that passes

Want to know what a governed workspace looks like — or test kibsu against one built to be read? Clone kibsu-lab: a complete fictional company (Tuppi Trading Co.) with a seeded deterministic data generator, an armed commit gate, a skills team for agents, and three machine-checkable tasks — including one that ships half-finished on a branch, so you can watch an agent resume work it never started. Point any coding agent at its AGENTS.md; check its work with one command. The lab scores 4 of 5 on the report above — and its README shows the exact command trail that proves it.


The five questions

question what it actually tests
1 Find your docs is there an index, or must an agent grep the whole tree on every task?
2 Know your conventions is there a consistent document shape to enforce, or does every file differ?
3 Prove they followed what fraction of your instructions could a reviewer verify afterwards?
4 Resume after a break do the files your instructions promise actually get produced?
5 Follow your own rules how often have your own commits broken your own written rule?

Question 5 is a replay, not an opinion. It walks your last N commits and asks, for each one, whether the index you claim to maintain would have gone stale. The answer is a count of your own commits, which is considerably harder to argue with than a score.


What "verifiable" means

An instruction is CHECKABLE if a reviewer could tell, from the repository alone, whether it happened:

  • it is a tick-box, or
  • it contains a runnable command, or
  • it names a concrete file artifact, or
  • it refers to an exit code, a diff, or an assertion

Everything else is CLAIMABLE: the only evidence it happened is the agent saying that it did.

The metric is deliberately biased toward CHECKABLE. Every ambiguous instruction is counted as checkable — a bare path mention counts, a bare command word counts. Reported figures are therefore ceilings. The true numbers are lower. python -m kibsu audit <dir> --definitions prints the whole ruleset so you can argue with it (exit 0).

Which lines

A percentage tells you there is a gap. It does not tell you where to look. explain lists the instructions behind report's number as path:line text — the shape an editor or a terminal turns into a link. (explain ships from package 0.10.0, which is also the first to carry scorer 0.11.0 and count sentences. The two numbering lines are easy to cross: scorer 0.10.0 shipped in package 0.9.0, so pip install kibsu==0.9.0 still measures in lines and prints the older figures.)

python -m kibsu explain /path/to/any/repo
python -m kibsu explain /path/to/any/repo --unit planner    # one file at a time

Real output, for one unit of kibsu-lab at commit 2d49abf:

  THE LINES BEHIND THE NUMBER
  /tmp/kibsu-lab
  --------------------------------------------------------------------------
  57.8% of your procedural instructions are verifiable: 26 of 45.
  3 instruction(s) can only be confirmed by the agent saying so:

  skills/planner/SKILL.md   3 of 8 cannot be checked
    skills/planner/SKILL.md:21  Create `docs/plans/<YYYY-MM-DD>-<slug>.md` with this shape:
    skills/planner/SKILL.md:46  Check off each task box (`- [ ]` -> `- [x]`) only after its own verify step passed, not when you...
    skills/planner/SKILL.md:54  Never soften a checker to make an unclear phase pass.
  --------------------------------------------------------------------------
  An instruction is CHECKABLE when a reviewer could confirm it from the repository
  alone: it is a tick-box, names a command to run, names a file, or names an exit
  code, a diff or an assertion. `python -m kibsu audit <dir> --definitions` prints the
  whole rule.
  Not every one should be. Judgement has nothing to check, and rewriting it as
  ceremony improves the number and worsens the instruction.
  What is counted is the SENTENCE, not the line: one wrapped over three lines is one
  entry, shown whole at the line it starts on. Where a paragraph's lines break
  changes neither this list nor the number.
  2 doctrine unit(s) not listed - checkability is not a fair test of them (--all-genres lists them).
  Nothing was written to this repo - run `git status` to confirm.

Reproduce it — the second line of the block is your clone's path; this one was run on Windows and is written here as the path the commands below use:

git clone https://github.com/M-Bajalan/kibsu-lab /tmp/kibsu-lab && cd /tmp/kibsu-lab && git checkout 2d49abf
python -m kibsu explain /tmp/kibsu-lab --unit planner

The verdict on every entry is the scorer's own, read back: one function decides both the percentage and the list, so the two cannot disagree. The number of entries listed is exactly the gap in the headline — 19 for this repository's 26 of 45 — and a test compares the two against a separate audit run rather than against explain's own arithmetic.

This sample is the reason the scorer counts sentences. Its first printing, under scorer 0.10.0, listed five entries for the same file at the same commit, and three of them were halves of sentences: verify step passed, not when you believe it should pass. was one. The scorer counted physical lines then, so a sentence wrapped over three lines was scored as each line that carried a directive word. A percentage had hidden that since the first scorer; printing the lines showed it on the first run, and 47.8% (22 of 46) is 57.8% (26 of 45) now that the same text is read as its author wrote it (see CORRECTIONS.md, 2026-10-11). One thing the sample still gets wrong is the instrument's, not the repository's: line 21 names a file and is listed anyway, because docs/plans/<YYYY-MM-DD>-<slug>.md is a path shape the scorer does not recognise. That one is in Honest limits.

Only procedure units are listed by default. A doctrine unit's 0% is the genre working, and a list of its lines would read as a to-do list for the one change that makes things worse. The output says how many units were held back; --all-genres lists them, --full lifts the display caps, and --json carries every instruction with both verdicts, the reason for each, and the lines it starts and ends on.

Genres, and why they matter

Scoring every document on checkability is the obvious way to get this wrong, so units are split first and procedure-only figures are reported separately:

genre describes is checkability a fair test?
procedure what to do, in order yes — this is the headline
doctrine how to think ("name the assumption before building") no. Produces judgement, not files. 0% here is the genre working, not a defect
persona who the agent is ("You are a senior Rust engineer…") no — it promises nothing
reference lookup material: tables, options, definitions partially

Genre is declared in frontmatter (genre: doctrine), not guessed. Auto-detection still runs as a fallback, and any disagreement between declaration and detection is printed — a declaration cannot quietly buy a better score.

That design exists because auto-detection failed. Ten numbered principles are structurally identical to ten numbered steps, and every heuristic tried turned out to be a prior belief expressed as a regular expression.

Phantom artifacts

Some instructions mandate an output file. Kibsu extracts those filenames and searches the working tree and the full git history for them. An artifact that has never existed, in any commit, is a phantom — an instruction no model has ever been caught skipping, because nothing was ever looking.

Scoped to artifacts a document claims are produced inside its own repository. Scaffolding instructions that generate files in the user's project are excluded, with the reason printed. On a shallow clone the result is UNKNOWN, never zero.


The survey

Eight public instruction collections, measured at pinned commits. Raw per-repo JSON, each carrying the SHA it was measured at, is in evidence/.

Regenerate the whole table yourself — one honesty note first: python -m kibsu survey clones each collection at its current HEAD, so on any day after the pinned date it measures newer commits and will legitimately print different numbers (that is how the first correction in CORRECTIONS.md was discovered). To reproduce this table's figures, check each clone out at the SHA recorded in its evidence/ JSON and point the survey at those clones:

python -m kibsu survey                    # today's HEADs - comparable method, newer data
# this table exactly: clone each repo, check out the sha from evidence/<slug>.json,
# then audit the pinned clones (SKILL_AUDIT_CLONES reuses them instead of re-cloning).
# Clone dirs MUST be named <owner>__<repo> (e.g. obra__superpowers) - any other name
# silently falls through to a fresh HEAD clone, the exact drift this note warns about:
SKILL_AUDIT_CLONES=/path/to/pinned-clones python -m kibsu survey

This section previously linked to an evidence/ directory that had never existed in any commit — a phantom artifact, in the README of a tool built to detect phantom artifacts. It was found by an outside reviewer, not by me, and not by four of my own review agents that had passed the same file. The directory now exists because the survey was actually re-run; see below for the one number that changed when it was.

repo sha units instr all% proc% phantom
davila7/claude-code-templates 91d14a7 891 20,099 14.6% 15.6% 56/129 (43%)
obra/superpowers 3dcbd5c 14 459 11.8% 13.1% 1/1
contains-studio/agents a5a480c 37 734 9.5% 9.7% —
sanjeed5/awesome-cursor-rules-mdc 8fbf269 5 230 7.8% 7.8% 2/3 (67%)
wshobson/agents c4b82b0 180 2,080 6.2% 7.4% 8/18 (44%)
vijaythecoder/awesome-claude-agents 2050f3c 33 293 8.2% 6.7% 1/4 (25%)
anthropics/skills b29e7cf 18 672 8.0% 6.2% 6/16 (38%)
VoltAgent/awesome-claude-code-subagents 947b44c 154 3,742 1.7% 1.7% 1/1

median procedure-only: 7.6% · min 1.7% · max 15.6% in-scope mandated artifacts: 172 distinct, 75 never existed in any commit (44%)

instr counts sentences, not lines, as of scorer 0.11.0. The phantom column is never existed / mandated in scope; — means the collection mandates nothing in scope.

These figures were re-measured 2026-10-11 with scorer 0.11.0, at the same pinned SHAs. The 0.11.0 round changed what is counted: the sentence, not the physical line. The median barely moved (7.5 -> 7.6) and that is not the result. Underneath it, individual collections moved by up to 1.6 points in both directions, and the mandated-artifact column moved most of all (229 -> 172 in scope, 96 -> 75 never existed): under the line count, a directive word in one sentence of a long line made every file named anywhere on that line a promise. 70 of the 78 mentions that left were pairings of that kind, classified by hand; 8 were real promises the stricter reading no longer sees, and 10 of the 20 that arrived are real. All of it, with the ones this round got wrong, is in CORRECTIONS.md. Before it, the 0.10.0 round (2026-09-01) came out of a pre-release audit of the three rounds before it: five verb/noun-ambiguous vocabulary entries stopped counting Note: ... callouts as instructions, and the median moved DOWN (7.7 -> 7.5) - many of those callouts carried a backtick command and had been counted checkable. Notes about commands are not commands. Before it, The 0.9.0 case round moved exactly one number: the existence check is byte-exact now

  • the answer git itself would give - and one mandate whose only instances differ by case became the phantom a Linux cat always said it was (95 -> 96). Before it, The 0.8.0 genre round moved almost nothing, and that is a published result, not a disappointment: the mandate rule reclassified 8 of 1,561 units (a doctrine label cannot sit on a unit that mandates files), two cells above shifted by a tenth of a point, and the median, the phantom counts and both preregistration workspaces are unmoved to the digit. The 0.7.0 round before it moved everything: The median moved again (9.4% → 7.7%) and every collection's percentage came down: four blind spots closed at once — the anchor now reads through markdown emphasis, the verb vocabulary grew by 55 census-approved entries, artifact extraction accepts the same optional delimiters checkability always did, and every mention of a mandate now counts toward its scope. Of the ~6,700 newly visible instructions, 97% are claimable — the blind spots overwhelmingly hid unverifiable instructions, so the older tables flattered every repo they measured, this project's own included. Every correction round, with its bias direction and the commands to reproduce both sides, is indexed in CORRECTIONS.md.

One number moved, and that is the point of the SHA column

(This section describes the first correction, 2026-07-29, kept as written. All corrections since — including the 2026-07-31 scorer fixes — are indexed in CORRECTIONS.md.)

An earlier revision of this table published 41 phantoms of 99 (41%) and carried no commit SHAs. Re-measuring produced 44 of 103 (43%).

Every checkable figure — units, instructions, all%, proc%, the median, min and max — matched exactly. The entire difference is the phantom-artifact count for davila7/claude-code-templates, the most actively maintained collection of the eight: 31/70 became 34/74 as the repository grew.

Nothing was wrong with the original measurement. It simply could not be reproduced, because it recorded no commit to reproduce it against — the same defect this tool reports as ? COULD NOT CHECK in other people's repositories. Both figures were probably right about different commits, and there was no way to tell.

Every row now carries the SHA it was measured at, and the raw per-repo JSON is in evidence/.

Two further repositories fell below the sample floor (≥5 procedure units and ≥50 procedure instructions). They are reported but not ranked: a percentage from fifteen instructions is noise wearing a number, and one of the two would otherwise have topped the table at 66.7% off a single unit.

The part that was not expected

One of the eight mandates zero artifacts. Not "promised and missing" — never promised anything at all. The field splits into two distinct failure modes: collections that make no verifiable claim in the first place, and collections whose claims fail — at rates from 25% to 100% per collection, 44% in aggregate. (This paragraph said three of the eight until 2026-10-11, and its own evidence/ had stopped agreeing with it before then: under scorer 0.10.0 one collection mandated nothing and a second mandated a single file that exists. Corrected with the 0.11.0 re-measurement; see CORRECTIONS.md. An earlier revision still said five of the eight — true under the old scorer. Two collections moved off that list for two different reasons, both checkable in evidence/: obra's one mandate was never missed — the old scorer extracted it, then the unit-level scaffold sweep excluded it; the line-level rule returns it to scope. sanjeed5's was genuinely invisible until .tsx joined the extension list. Both turned out phantom — two collections moved from the first failure mode into the second.)


Verify it yourself

You are about to point a tool at your own repository. Here is everything you can check first, without taking anything here on trust.

Nothing to install, nothing to audit. pyproject.toml declares dependencies = [], and the test suite imports nothing outside the standard library either. There is no transitive dependency tree to review, because there is no dependency tree.

python -c "import pathlib,sys; sys.exit(0 if 'dependencies = []' in pathlib.Path('pyproject.toml').read_text() else 1)"
echo $?                  # 0        (bash / zsh)
echo $LASTEXITCODE       # 0        (PowerShell)

One line rather than a heredoc, because a heredoc is a bash construct and this line has to work in PowerShell too — a "verify it yourself" section that only verifies on Unix is half a claim.

It is small enough to actually read. 6,644 lines across 15 files in kibsu/, plus 7,217 lines of tests running 316 cases. That is an evening, not a quarter. Count it yourself rather than believing this paragraph — this is the third revision of these numbers to ship after the code had already grown past them (#29 indexes the incident), so the commands below outrank the prose above them - and as of #29's fix the test suite enforces that agreement (tests/test_readme_counts.py runs the same measurements and fails while this paragraph is stale):

python -c "import pathlib,sys; f=sorted(pathlib.Path(sys.argv[1]).glob('*.py')); print(len(f),'files',sum(len(p.read_text(encoding='utf-8').splitlines()) for p in f),'lines')" kibsu
python -m unittest discover -s tests   # prints the case count

An earlier revision published 3,679 here. That figure was not invented — it was measured, and then re-measured by a second reviewer who got the same answer. Both used PowerShell's Measure-Object -Line, which silently skips empty lines: 4,241 total minus 562 blank lines is exactly 3,679. Two counts agreed because they were not independent, which is the failure the second count existed to prevent. The commands above are printed so the next reader does not have to trust an instrument they cannot see.

git clone https://github.com/M-Bajalan/kibsu && cd kibsu
python -m unittest discover -s tests    # exit 0
python -m kibsu report .                # no install step, no config, no network

report exits 0 when every question came back ready and 3 when something is not ready or could not be checked. Both are successful runs — 3 is a finding, not a crash. (Pointed at this repository it returns 3, and the reason is stated in Honest limits.)

The diagnostic commands do not write to your repository. This is the design constraint everything else bends around — scoped honestly: index, install/gate --install, and check --receipt write exactly the artifacts they exist to write, opt-in, named in their own --help; every diagnostic (report, explain, audit, discover, survey, guide, learn) writes nothing, and that claim is two commands to falsify:

python -m kibsu report /path/to/your/repo
git -C /path/to/your/repo status --porcelain

The second command prints nothing. If it ever prints something, that is a bug worth an issue. Note the ;-style separation rather than &&: chaining on && would skip the proof precisely when report returns 3, which is most of the time and is the case you most want proven.

The published package has verifiable provenance. Releases go to PyPI through GitHub's Trusted Publishing (OIDC), which generates PEP 740 attestations tying each artifact to the exact workflow run and commit that built it — visible on the PyPI project page. No API token exists for this project, in CI settings or anywhere else; release.yml explains why.

Two outside scanners look at this code, and their findings are public. CodeQL scans the Python and the workflow files on every push and weekly; results appear in the Security tab whether they are flattering or not. OpenSSF Scorecard rates the release path — branch protection, token permissions, pinned dependencies — and publishes the number to a public dataset recomputed by someone else's infrastructure. That is what makes the badge worth having; a badge served from this repository would be decoration.

What those two do not tell you: Scorecard measures process, not correctness. A good score means the release path is hard to tamper with. It says nothing about whether the numbers this tool reports are right — that is what the SHAs in evidence/ and the Honest Limits below are for. Confusing the two is precisely the error this project was built to name.

What you cannot verify from here: the provenance scrub described in PROVENANCE.md is not in this repository and will not be — the denylist it scans for is itself the sensitive artifact. What you can check is the absence it claims: search this tree for anything resembling a company, a market, a customer or an internal system. Finding none is a falsifiable result, and it does not require the tool.

The improvement experiment on the team skills is pre-registered — baseline, falsifiable predictions, and the standing rule that a rising doctrine score is disqualifying: PREREGISTRATION.md, committed before any skill was rewritten.

Contribution rules — including the four that are non-negotiable — are in CONTRIBUTING.md.


Honest limits

Read these before quoting anything above.

  • obra/superpowers ships a separate eval harness that drives real agent CLIs and grades whether a skill was followed. Kibsu reads only documents, so it cannot see that. The real enforceability of that repo is higher than 13.1%. This is the strongest counter-example to the entire approach, and it belongs at the top of the limits rather than buried at the bottom.
  • The metric is a heuristic. Biased generous by design. Ceilings, not measurements.
  • What is counted is the sentence, and the cut is conservative on purpose. Through scorer 0.10.0 it was the physical line, which scored a hard-wrapped sentence once per line that carried a directive word; 0.11.0 reads a paragraph, list item or blockquote the way Markdown renders it and cuts it into sentences. What that leaves, each one measured or tested rather than assumed:
    • A missed boundary merges two sentences; it never invents one. A boundary needs sentence punctuation followed by a capital letter or a code span, so a sentence that opens in lower case, e.g. Foo, and a run of initials are left whole. The rule knows English capitals only.
    • Lines with no blank line, list marker or punctuation between them are one sentence, exactly as a renderer would run them together. Six lines that each open with ✅ are one paragraph to Markdown and one sentence here.
    • An imperative behind a label is seen only by its modal. **Pro tip:** Create a setup script does not open with its verb, so it counts as an instruction only when the sentence also carries must, never or the like. Reading the colon as a boundary would find them, and was measured on a draft of this reader: about 2,000 more instructions in the largest collection, nearly all of them claimable, and a median near 5.6% instead of 7.6%. Left out as a round of its own - it changes what an instruction is, not what is counted.
    • A tick-box item counts once, however many sentences it holds: one box, one promise.
    • In two places the file is read as its reader sees it, not as a renderer would: a fence on the line under a tag (<Good> then a fence) is a fence, and a pipe table is a table even when its delimiter row has the wrong number of cells (1 table in 1,241 here).
    • A mandated file is read from a sentence that is itself an instruction. Of the 78 file mentions that stopped counting as promises in this page's survey, 70 were a verb in one sentence paired with a file in another, and 8 were real: After collecting results from all subagents, combine them and write to <planning_dir>/claude-research.md is not seen as an instruction, because it does not open with its verb. Named one by one in CORRECTIONS.md, 2026-10-11.
    • Where a soft line break falls inside a block changes no number. Held by a property test in the suite, after a fuzz that re-wrapped all 1,477 surveyed files against an independent CommonMark parser: no instruction count, checkable count or sentence moved; in the two reader-over-renderer places above, 4 files can still change a genre signal. A smaller sibling from explain's first listing: a templated path written with angle brackets (docs/plans/<date>-<slug>.md) is not read as naming a file.
  • Persona collections are not badly written, they are a different genre. Scoring them on checkability was the first mistake this tool made.
  • Low checkability has not been shown to produce worse outcomes. Nobody has demonstrated that. The demonstrated finding is that nobody can tell either way — the weaker claim, the more defensible one, and the only one worth acting on.
  • N is small for several repositories. Sample floors are enforced, not assumed.
  • Genre auto-detection is weak. Declare it.
  • This repository scores 0 of 5 on its own report, and the number is honest. Run python -m kibsu report . here and you get 0 of 5 ready. 3 could NOT be checked — worse than every collection in the survey table. The reason is that kibsu is a tool, not an instruction collection: there is no AGENTS.md, no skills/, and no index, so three of the five questions have nothing to measure and say so rather than scoring zero. That is the ? mark doing its job on its own author. It is also the strongest argument for the write-side work that is next on the roadmap — a tool that cannot yet furnish the artifacts it asks other repositories for. Anyone using this against the project is making a fair point, and it is written here first so they do not have to.
  • The Scorecard badge above says 4.8, and one of the points it deducts is for a genre mismatch — which is this project's own argument, arriving inside its own badge. Dependency-Update-Tool: 0, because there is no Dependabot config for Python packages. There are no Python packages. dependencies = [] is the first hard rule in CONTRIBUTING.md, so the only possible score on a check for keeping dependencies updated is zero, permanently, by design. Scoring a repository on a dimension it deliberately does not have is exactly the mistake this tool made first and now reports in others: the metric is measuring the wrong genre. Adding a config block that can never fire, to move a number, would have been the Goodhart response. What made it interesting is that the check was also right about something it did not say. CI actions are dependencies too, and those were genuinely unwatched — so .github/dependabot.yml now exists for the github-actions ecosystem only, and every action in every workflow is pinned to an immutable commit SHA it keeps current. Wrong about the thing it named, right about a thing it pointed at. That is a better outcome than either obeying it or dismissing it, and it is the argument for reading a low score instead of chasing it. One more thing worth borrowing rather than criticising: two of Scorecard's checks return -1, meaning could not be checked — not zero. It reaches for the same three-state honesty this tool argues for with its ? mark, on the same kind of question. A rating system that distinguishes bad from unknown is doing something most do not.

The name

kibsu (𒆠𒍑, KI.UŠ) is Akkadian, derived from kabāsu, "to tread":

1. "tread, imprint" of a foot — kibsu redû, "to follow a track"; ša kibsi, "tracker" 2. "track, route"; transferred, "mode of life, behaviour, course of life" 3. mathematical: "way of calculation"

— A Concise Dictionary of Akkadian, Black, George & Postgate, Harrassowitz ²2000

The trace left behind, the course of conduct, and the method of reckoning. The tool is all three.

License

MIT. See LICENSE and PROVENANCE.md.

Metadata

Release files for kibsu 0.10.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for kibsu 0.10.0
File Size Uploaded
kibsu-0.10.0.tar.gz 401.1 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for kibsu 0.10.0
File Interpreter ABI Platform
kibsu-0.10.0-py3-none-any.whl Python 3 none any Details

Total release size: 544.6 kB

Release files / kibsu-0.10.0.tar.gz

Download URL kibsu-0.10.0.tar.gz
Size 401.1 kB
Tags Source
SHA-256 checksum
How to use checksums
1b9156e20823b7edb61e29810ef1a169021ff851a17bc07cd7f6d3965750030b
BLAKE2b-256 checksum
How to use checksums
387d04e0d9925d53d253072abd78023e497ad835300461d4e1961b546a750ab4
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Oct 11, 2026.

Transparency log

Release files / kibsu-0.10.0-py3-none-any.whl

Download URL kibsu-0.10.0-py3-none-any.whl
Size 143.4 kB
Tags Python 3
SHA-256 checksum
How to use checksums
4d6c38ddae4fcae1a1293b7b564f44945ee256ea8343a7a3977117014eda3752
BLAKE2b-256 checksum
How to use checksums
18025488ca1499f51e22c6e446da5c3ebbcb5ddeadb57e76dc0dafaf3ab2c9cc
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Oct 11, 2026.

Transparency log

Release history Release notifications | RSS feed

This release

0.10.0 This release

2 release files

0.9.0

2 release files

0.8.0

2 release files

0.7.0

2 release files

0.6.0

2 release files

0.5.0

2 release files

0.4.0

2 release files

0.3.0

2 release files

0.2.1

2 release files

0.2.0

2 release files

0.1.1

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page