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Change tracking for AI-era codebases

Project description

Selvedge

Tests PyPI License: MIT

Long-term memory for AI-coded codebases. A git blame for AI agents — but for the why, not just which line which model touched. Captured live, by the agent, as the change happens.


Six months ago, your AI agent added a column called user_tier_v2. You don't know why. git blame points to a commit from claude-code with a generated message that says "Update schema." The session that made the change is long gone — and so is the prompt that produced it.

With Selvedge, you run this instead:

$ selvedge blame user_tier_v2

  user_tier_v2
  Changed     2025-10-14 09:31:02
  Agent       claude-code
  Commit      3e7a991
  Reasoning   User asked to add a grandfathering flag for legacy free-tier
              users during the pricing migration. Stores the original tier
              so we can backfill discounts without touching billing history.

That reasoning was captured by the agent in the moment — written into Selvedge from the same context that produced the change. Not inferred from the diff afterward by a second LLM. Not a hand-typed commit message.



Who Selvedge is for

Selvedge has two audiences. Same tool, same pip install, same SQLite file under .selvedge/. Different scale of pain.

Teams running long-term, AI-coded codebases. When the project is big enough that you (or someone else) will touch it again in six months, twelve months, three years — but most of it was written by an agent whose context evaporated the day each PR shipped. git blame tells you what changed. Selvedge tells you why — even after the agent session, the prompt template, the developer who asked for it, and the model version are all long gone. This is the original use case: production codebases, schema decisions, migrations, dependency changes that need an audit trail that survives turnover.

Solo developers using Claude Code on everyday projects. Side projects, weekend builds, the small internal tool you keep poking at. You don't need enterprise governance — you just need to remember why you (or your agent) did the thing you did yesterday, last week, last sprint. Run selvedge init once. Add four lines to your CLAUDE.md. From then on, selvedge blame is muscle memory — a way to talk to your past self when your past self was an LLM.

If you've ever come back to your own AI-built project and thought "what was this for again?", Selvedge is the missing piece.


The problem

Human-written code leaks intent everywhere — commit messages, PR descriptions, inline comments, the Slack thread that preceded it. AI-written code doesn't. The agent has perfect clarity about why it made each decision, but that context lives in the prompt and evaporates when the conversation ends.

Six months later, your team is debugging a schema decision with no trail. git blame tells you what changed and when. It can't tell you why.

Selvedge captures the why — live, by the agent itself, as the change is made. The diff is git's job. The why is Selvedge's.


What's new in v0.3.3

A discoverability + ergonomics release. No new MCP tools, no behavior changes that affect stored data — but the live tool schema is now substantially richer for the agents that call it and the directories that score it. Drop-in upgrade for anyone on 0.3.2.

Per-parameter descriptions on every tool. All 6 MCP tools now declare each parameter via Annotated[T, Field(description=...)], populating the per-parameter description field in tools/list. Previously each parameter shipped only type and title; the rich docstrings sat in the function body where agents couldn't see them at tool-call time. Coverage went 0/21 → 21/21. Agents picking which tool to call read these directly, so it's a DX win for Claude Code / Cursor use — not just a directory-score win.

MCP tool annotations. Each tool now declares readOnlyHint, destructiveHint, idempotentHint, openWorldHint, and a human-friendly title. log_change is the only writer (append-only, not idempotent — each call mints a new event). The five readers (diff, blame, history, changeset, search) are read-only and idempotent. None are open-world. Lets MCP clients gate or surface the tools appropriately.

Output schemas on every tool. New LogChangeResult and BlameResult TypedDicts give the JSON-RPC layer concrete output schemas to advertise — was missing on the two dict-returning tools. The list-returning ones already had auto-generated schemas, so all 6 are now consistent.

Custom server icon. A "stitched timeline" mark — a horizontal running stitch where each visible stitch is a captured change event. Lives at assets/icon.svg and a 512×512 assets/icon.png, shipped in the Smithery bundle.

log_change and blame return stable shapes. log_change now always returns id, timestamp, status, error, and warnings keys (with empty values when not applicable) — easier to type-check without branching. blame does the same on miss: every event field is empty, error carries the "no history found" message. Same conventions as before, just consistent payloads.

CLAUDE.mddocs/architecture.md split. CLAUDE.md is now a slim agent-instructions file (sources of truth, code conventions, version bump checklist). Architecture, data model, MCP tool reference, full CLI reference, and the phase plan all moved to docs/architecture.md.

See CHANGELOG.md for the full list and reasoning.


What's new in v0.3.2

An observability-polish release. No new feature surface — the focus is making existing functionality discoverable and debuggable, plus locking in WAL/busy_timeout assumptions across SQLite versions. Drop-in upgrade for anyone on 0.3.1.

selvedge doctor. A single health-check that walks the ambient state agents typically run into and reports each row PASS / WARN / FAIL / INFO: which DB path is being resolved (and which precedence step matched — SELVEDGE_DB, walkup, or global fallback), whether .selvedge/ exists, whether the schema is at the latest migration version, whether the post-commit hook is installed and not silently failing, last tool_calls timestamp (proxy for "is the agent wired up?"), and whether SELVEDGE_LOG_LEVEL is set to a recognized value. Exits 1 on any FAIL, so doctor can be wired into CI. --json for machine-readable output.

$ selvedge doctor
Selvedge doctor

  Check                  Status      Detail
 ───────────────────────────────────────────────────────────────────
  Database path          i INFO      ~/.selvedge/selvedge.db  [via SELVEDGE_DB env var]
  .selvedge/ directory    PASS      ~/.selvedge
  Schema version          PASS      at v2 (latest)
  Post-commit hook        PASS      ~/code/myapp/.git/hooks/post-commit
  Last hook failure       PASS      no failures recorded
  MCP wiring              PASS      last tool_call at 2026-04-25T14:21:08Z
  SELVEDGE_LOG_LEVEL     i INFO      unset (defaults to WARNING)

All checks passed.

Post-commit hook no longer fails silently. The previous hook silently died when selvedge wasn't on the PATH that git launched (a common symptom under macOS GUI git clients with stripped PATHs). The new hook appends a single line to .selvedge/hook.log on failure, and both selvedge status and selvedge doctor surface the most recent failure. Old hooks keep working — re-running selvedge install-hook upgrades to the new wrapper.

selvedge stats upgrades. The coverage report now breaks calls down per-agent so you can catch the case where claude-code is logging changes but cursor is only querying history. A separate missing_reasoning count surfaces stored events whose reasoning fails the quality validator — empty, too short, or a generic placeholder the agent shipped despite the warning.

Pinned-SQLite CI matrix. A new CI job builds SQLite 3.37.2, 3.42.0, and 3.45.3 from source and runs the suite against each via LD_PRELOAD, locking in WAL + busy_timeout behavior across the SQLite versions selvedge users are most likely to be on. The Python matrix also gains 3.13.


How Selvedge compares

There's a fast-growing "git blame for AI agents" category. Here's where Selvedge fits — and where it deliberately doesn't.

Reasoning source Granularity Mechanism Grouping Storage
Selvedge Captured live, by the agent in the same context that produced the change Entity — DB column, table, env var, dep, API route, function MCP server — agent calls it as work happens Changesets — named feature/task slugs across many entities SQLite, zero deps
AgentDiff Inferred post-hoc by Claude Haiku from the diff at session end Line Git pre/post-commit hook None JSONL on disk
Origin Captured at commit time Line Git hook None Local
Git AI Attribution metadata Line Git hook + Agent Trace alliance None Git notes
BlamePrompt Prompt-only Line Git hook None Local

Why "captured live" matters. AgentDiff and Origin generate reasoning after the change is made, by feeding the diff back to a second LLM call. Selvedge's reasoning is the agent's own intent, written from the same context window that produced the change — no inference, no hallucinated explanations, and an empty reasoning field is itself a useful signal (the agent didn't have one).

Why "entity-level" matters. Most tools attribute lines. Selvedge attributes things you actually search for: users.email, env/STRIPE_SECRET_KEY, api/v1/checkout, deps/stripe. The first question after git blame is usually "what's the history of this column", not "what's the history of lines 40–48 of users.py".

Why "changesets" matter. A Stripe billing rollout touches the users table, two new env vars, three new API routes, one dependency, and four functions across the codebase. Tag every event with changeset:add-stripe-billing and you can pull the entire scope back later — even if the original PR was broken into eight smaller ones over a month.

Selvedge ↔ Agent Trace. Agent Trace (Cursor + Cognition AI, RFC Jan 2026, backed by Cloudflare, Vercel, Google Jules, Amp, OpenCode, and git-ai) is an emerging open standard for AI code attribution traces. Selvedge isn't a competitor to it — it's a compatible producer. The design for selvedge export --format agent-trace is at docs/agent-trace-interop.md. Agent Trace is the wire format. Selvedge is the live capture + query layer that emits it.


Install

pip install selvedge

Quickstart

1. Initialize in your project

cd your-project
selvedge init

2. Add to your Claude Code config

~/.claude/config.json:

{
  "mcpServers": {
    "selvedge": {
      "command": "selvedge-server"
    }
  }
}

3. Tell your agent to use it

Add to your project's CLAUDE.md:

You have access to Selvedge for change tracking.
Call selvedge.log_change immediately after adding, modifying, or removing
any DB column, table, function, API endpoint, dependency, or env variable.
Set `reasoning` to the user's original request or the problem being solved.
Set `agent` to "claude-code".
Before modifying an entity, call selvedge.blame to understand its history.

4. Query your history

selvedge status                        # recent activity + missing-commit count
selvedge diff users                    # all changes to the users table
selvedge diff users.email              # changes to a specific column
selvedge blame payments.amount         # what changed last and why
selvedge history --since 30d           # last 30 days of changes
selvedge history --since 15m           # last 15 minutes ('m' = minutes)
selvedge changeset add-stripe-billing  # all events for a feature/task
selvedge search "stripe"               # full-text search
selvedge stats                         # log_change coverage report
selvedge install-hook                  # auto-link commits to events
selvedge import migrations/            # backfill from migration files
selvedge export --format csv           # dump history to CSV

How it works

Selvedge runs as an MCP server. AI agents in tools like Claude Code call Selvedge's tools as they work — logging structured change events to a local SQLite database.

Each event records:

  • What changed (entity path, change type, diff)
  • When (timestamp)
  • Who (agent, session ID)
  • Why (reasoning — captured from the agent's context in the moment)
  • Where (git commit, project)

The diff is git's job. The why is Selvedge's.


Entity path conventions

users.email           DB column (table.column)
users                 DB table
src/auth.py::login    Function in a file (path::symbol)
src/auth.py           File
api/v1/users          API route
deps/stripe           Dependency
env/STRIPE_SECRET_KEY Environment variable

Prefix queries work everywhere: users returns users, users.email, users.created_at, and any other entity under the users. namespace.


MCP tools

When connected as an MCP server, Selvedge exposes:

Tool Description
log_change Record a change event with entity, diff, and reasoning
diff History for an entity or entity prefix
blame Most recent change + context for an exact entity
history Filtered history across all entities
changeset All events grouped under a named feature/task slug
search Full-text search across all events

CLI reference

selvedge init [--path PATH]               Initialize in project
selvedge status                           Recent activity summary
selvedge diff ENTITY [--limit N]          Change history for entity
selvedge blame ENTITY                     Most recent change + context
selvedge history [--since SINCE]          Browse all history
              [--entity ENTITY]
              [--project PROJECT]
              [--changeset CS]
              [--summarize]
              [--limit N]
selvedge changeset [CHANGESET_ID]         Show events in a changeset
                  [--list]                or list all changesets
                  [--project NAME]
                  [--since SINCE]
selvedge search QUERY [--limit N]         Full-text search
selvedge stats [--since SINCE]            Tool call coverage report (per-tool, per-agent)
selvedge doctor [--json]                  Health check: DB path, schema, hook, MCP wiring
selvedge install-hook [--path PATH]       Install git post-commit hook
                     [--window MIN]       (default 60 minutes)
selvedge backfill-commit --hash HASH      Backfill git_commit on recent events
                        [--window MIN]    (default 60 minutes)
selvedge import PATH                      Import migration files (SQL / Alembic)
              [--format auto|sql|alembic]
              [--project NAME]
              [--dry-run]
selvedge export [--format json|csv]       Export history to JSON or CSV
              [--since SINCE]
              [--entity ENTITY]
              [--output FILE]
selvedge log ENTITY CHANGE_TYPE           Manually log a change
             [--diff TEXT]                CHANGE_TYPE: add, remove, modify,
             [--reasoning TEXT]           rename, retype, create, delete,
             [--agent NAME]               index_add, index_remove, migrate
             [--commit HASH]
             [--project NAME]
             [--changeset CS]

All read commands support --json for machine-readable output.

Relative time in --since:

  • 15m → last 15 minutes (m = minutes)
  • 24h → last 24 hours
  • 7d → last 7 days
  • 5mo → last 5 months (mo or mon = months)
  • 1y → last year

Unparseable inputs (e.g. --since yesterday) exit with a clear error rather than silently returning empty results. ISO 8601 timestamps are also accepted and normalized to UTC.


Configuration

Method Format Example
Env var SELVEDGE_DB=/path/to/db Per-session override
Project init selvedge init Creates .selvedge/selvedge.db in CWD
Global fallback ~/.selvedge/selvedge.db Used if no project DB found

Coverage checking

Wondering how often your agent actually calls log_change? Two ways to check:

# Quick summary in the terminal
selvedge stats

# Cross-reference against git commits
python scripts/coverage_check.py --since 30d

The coverage script compares your git log against Selvedge events and shows which commits have associated change events. Low coverage usually means the system prompt needs strengthening — see docs/fallbacks.md for guidance.


Contributing

git clone https://github.com/masondelan/selvedge
cd selvedge
pip install -e ".[dev]"
pytest

See CLAUDE.md for architecture details and the phase roadmap.


License

MIT — see LICENSE.

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