Selvedge

selvedge.sh · DevHunt · PyPI · GitHub

Persistent decision memory for AI agents.

Save why you chose an approach, what you rejected, and what would change your mind. Retrieve that context in the next coding session, using a function, database column, API route or dependency as the lookup key.

Selvedge is for anyone using a compatible agent. Connect through local MCP over stdio, or use the CLI from an agent with shell access. Decisions stay in the same SQLite store in .selvedge/ when you switch tools. No hosted account is required; core storage and retrieval make no LLM calls.

Get started · Documentation · Agent compatibility

uv tool install --upgrade selvedge

selvedge demo

Requires uv and Python. Python 3.11–3.14 is recommended; Python 3.10 remains compatible but is end of life. The demo uses a temporary database. Follow the quickstart to connect your agent to a real project.

Use selvedge demo --mcp to save through a local stdio MCP server, restart it and retrieve the same record. Add --json for the checked IDs and versions. This tests the Python installation running Selvedge with disposable data; your agent's configuration, activation and hooks still need a separate check.

Who Selvedge is for

• Solo developers returning to a project after the original conversation is gone.
• Teams that need to pass recorded decisions between sessions and coding tools.

The problem

Code shows the chosen approach. It may leave out the constraint that shaped it or the alternative you ruled out. Selvedge gives those explanations a place in the project and tools to retrieve them before the next edit.

Only explicitly saved decisions can be recalled. A saved explanation is an account supplied by a person or agent; Selvedge does not verify that it is true or guarantee that an agent will consult it. Verify one decision across two sessions to test your setup.

What's new in v0.3.18

Read the recorded reasons before routine review metadata. The optional GitHub review Action puts rejected and reverted approaches, revisions and constraints first. Its comment defaults to a 6,000-character budget, counts omitted events and links to the trusted base store and longer job summary. Unchanged reruns leave the comment untouched.

Healthy runs with no matching history keep the job summary without creating a new comment; an existing comment is refreshed and broken chains remain visible. Missing history is unknown, not approval. The Action still uses only publication-approved base history and never executes PR-head code.

A regression check also protects the library's local save/reopen/retrieve path with site packages unavailable and socket access blocked. No new runtime dependencies, migrations, MCP tools or model calls. Python 3.10 compatibility is retained; use supported Python 3.11–3.14 for new installations. Native Action execution and review usefulness remain unverified.

What's new in v0.3.17

Check recorded decisions before a review. Generate a Markdown digest, then run selvedge export --format markdown -o DECISIONS.md --check to catch drift. An identical digest exits 0 silently; a stale or missing digest exits 1 with a unified diff and regeneration guidance. Check mode preserves the digest and stored records. Review exported reasoning before publishing it.

selvedge demo --mcp saves a synthetic rejection through a real local MCP server, restarts it and retrieves the same record. It uses disposable state; it does not verify your agent's configuration or hook activation.

CLI output now preserves literal brackets in user data, and blame and Markdown exports distinguish rejected approaches from changes that were tried and reverted. Python 3.10 compatibility remains for this patch, but that runtime is now upstream end of life; use tested, supported Python 3.11–3.14 for new installations. No new runtime dependencies, migrations or MCP tools.

Where Selvedge fits

1. Save a decision. You or your coding agent record a choice, its reason, and any rejected approaches through MCP or the CLI.
2. Keep it with the project. Selvedge stores the record in local SQLite, keyed to the function, column, route or other entity it concerns.
3. Recall it before the next edit. A later session queries the same store and checks whether the earlier constraint still applies.

Git keeps the code history; review tools check changes; observability shows runtime behavior. Selvedge adds the recorded reasons behind decisions. How it works · Agent Trace interchange

How Selvedge compares

Choose the simplest memory mechanism that fits your workflow:

These approaches can be used together. Read the source-linked comparison and instructions versus ADRs versus decision memory for specific selection criteria and limitations.

Why entity history matters. users.email, env/STRIPE_SECRET_KEY, api/v1/checkout and deps/stripe remain useful query targets when their code moves. Explicit rejection and superseding records let a later session inspect what was tried and whether the original constraint still applies.

Why capture time matters. Recording a reason while the context is available can preserve information a diff does not contain. It does not make the reason infallible. Retrieval uses stored records; the coding agent remains responsible for checking applicability and testing its change.

Why changesets matter. Tag events with a shared changeset such as add-stripe-billing to retrieve a task's decisions across tables, environment variables, routes and functions.

Agent Trace interchange. selvedge export --format agent-trace and selvedge import --format agent-trace exchange Agent Trace v0.1.0 records. Reasoning and entity history travel in the dev.selvedge metadata. The mapping and limits document the format; Selvedge vendors the schema and has no runtime dependency on the upstream project.

Quickstart

Connect your agent

With uv installed:

uv tool install --upgrade selvedge

selvedge demo cd your-project selvedge setup

Setup detects supported clients. To select a preset explicitly, use --agent with claude-code, codex, copilot, cursor, gemini or windsurf; repeat the flag for multiple clients. These presets are conveniences, not a compatibility limit. For another agent with local stdio MCP support, follow manual setup. Agents with shell access can use the CLI. Prefer pip? Use python -m pip install --upgrade selvedge in a virtual environment. The selvedge-server executable must be on your editor's PATH; launch the editor from that environment or use the executable's absolute path in its MCP config.

Setup asks before changing files, backs up existing content, installs MCP and agent instructions, initializes the project, and offers a Git post-commit hook. Configuration files and lifecycle hooks vary by client. See the compatibility guide for preset paths, activation requirements and limitations.

Restart your agent in the project and approve Selvedge's tools if prompted. Follow your client's project-trust requirements. Ask the agent:

Use Selvedge to record one real approach we considered and rejected in this project.

Include the entity, why, and what would change our mind. Do not invent a decision.

Show the saved entity path and record ID.

Start a new session and look up the same entity to verify that the decision carries forward. Follow the first-decision verification guide and cross-agent handoff guide for observable checks. MCP access does not automatically capture every decision: the installed instructions guide the agent to use it. Native lifecycle adapters cover supported client events; startup delivery, watched-edit checks and compaction notifications vary by harness. See the agent hook guide before enabling them.

For CI bootstrap or devcontainer.json postCreateCommand:

selvedge setup --non-interactive --yes

Verify the wiring — open a second terminal in the same project:

selvedge watch

Make any change in your AI tool — add a column, rename a function, add an env var. selvedge watch should print the new event within a second of the agent calling log_change. If nothing arrives, run selvedge doctor for a single-command health check that tells you which step is silently broken.

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 # observed tool calls and explanation quality selvedge import migrations/ # backfill from migration files selvedge export --format csv # dump history to CSV

Manual install — if you'd rather wire it up yourself

If you don't want to run the wizard,