Resume Matcher, driven by you

You are the AI. The resume-matcher command stores, validates, scores and renders what you write, in the same database as the web app, so everything you save appears at http://localhost:3000. The user makes small edits there.

Work in this order: set up (once), master resume (once), tailor (per job), hand off to the UI. Skip a step that is already done. Talk to the user in their language.

The command

From the repository root:

uv run --directory apps/backend resume-matcher <tool> [arguments]

• resume-matcher --help lists the tools; resume-matcher <tool> --help shows one tool's arguments as a JSON schema.
• Arguments are either one JSON object ('{"resume_id": "…"}', @args.json, or - for stdin) or fields: key=value (string), key=@file (string from a file), key:=json (any JSON value), key:=@file.json (JSON from a file).
• Use absolute paths. --directory runs the command from apps/backend, so a relative path resolves from there.
• The result is JSON on stdout. Exit code 1: the tool failed and stderr says why. Exit code 2: the command line was wrong.
• Write argument files (large JSON such as a whole resume) to jobs/.work/ in this repository (mkdir -p jobs/.work first). It is gitignored and inside every agent's sandbox.
• To shorten it, define a shell function, not a variable (zsh does not split a command stored in a variable): rmx() { uv run --directory "$PWD/apps/backend" resume-matcher "$@"; }

Docker install: run the same tools inside the container, from its backend folder so they use the app's data:

docker exec -i -w /app/backend resume-matcher python -m app.mcp_server.cli <tool> [arguments]