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How to inspect a labeled skill ranking offline first with Skillranker

Run the built-in fixture demo and readiness checks before sharing any real session.

Who it is forA cautious developer or team lead who wants to see how SkillRanker behaves before giving it any private conversation data.

The problemConnecting a live session to a ranking service means sharing context, and you want to understand the output format and setup gaps first.

The outcomeYou see a labeled fixture result, confirm which adapters and integrations your build supports, and get a dry-run preview of the redacted request with no network calls.

What you need first

  • Linux or macOS with a local filesystem that supports Unix permissions
  • Your own credential for a Jev-compatible provider, such as TypeSafe_API_KEY for TypeSafe.ai or Cloudflare account settings
  • Rust toolchain for a source build, or the installer's prerequisites: Bash, Python 3, curl, and sha256sum or shasum
  • Explicit consent to send selected session context over the network for live ranking

Steps

  1. Install sr with cargo install --locked --path . --bin sr.
  2. Run sr demo --case useful to see a labeled fixture result without a key, network, or private session.
  3. Run sr doctor --json and sr capabilities --json to check configuration and available adapters.
  4. Run sr roster --json to inspect visible, shadowed, and excluded skill records.
  5. Preview the redacted wide-pass request with sr rank --context scratch/context.json --dry-run.

Prompt for your agent

Using the Dicklesworthstone/skillranker repo, run `sr demo --case useful` and `sr rank --context <context file> --dry-run`. Expected output: a labeled fixture result and a redacted request preview with no network call. Verify that the preview contains no API key or secret values before sharing it further.

Caveat. The demo uses an offline fixture, so it shows the result format and not how the ranking performs on your own skill library.

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