Skip to main content

Evaluation-driven Claude Code skill development

Project description

skillet

CI License Python

Evaluation-driven Claude Code skill development.

Install

pip install pyskillet

Why

Anthropic recommends building evaluations before writing skills:

Create evaluations BEFORE writing extensive documentation. This ensures your Skill solves real problems rather than documenting imagined ones.

But they don't provide tooling:

We do not currently provide a built-in way to run these evaluations.

skillet fills that gap.

Workflow

1. Capture evals with /skillet:add

When Claude does something wrong, capture it:

> Write a code review comment for this SQL query...

Claude: This code has a SQL injection vulnerability...

> /skillet:add

Claude: What did you expect instead?

> Should start with **issue** (blocking): using conventional comments format

Claude: Eval saved to ~/.skillet/evals/conventional-comments/001.yaml

2. Run baseline eval

skillet eval conventional-comments
Eval Results (baseline, no skill)
==================================
Evals: 5
Samples: 3 per eval
Total runs: 15

Pass rate: 0% (0/15)

3. Create the skill

skillet new conventional-comments
Found 5 evals for 'conventional-comments', drafting SKILL.md...

Created ~/.claude/skills/conventional-comments/
└── SKILL.md (draft from 5 evals)

4. Eval with skill

skillet eval conventional-comments ~/.claude/skills/conventional-comments
Eval Results (with skill)
=========================
Skill: ~/.claude/skills/conventional-comments
Evals: 5
Samples: 3 per eval
Total runs: 15

Pass rate: 80% (12/15)

5. Tune the skill

skillet tune conventional-comments ~/.claude/skills/conventional-comments
Round 1/5: Pass rate 80% (12/15)
  Improving skill...
Round 2/5: Pass rate 93% (14/15)
  Improving skill...
Round 3/5: Pass rate 100% (15/15)
  Target reached!

Best skill saved to ~/.claude/skills/conventional-comments/SKILL.md

Commands

skillet eval <name>              # baseline eval (no skill)
skillet eval <name> <skill>      # eval with skill
skillet new <name>               # create skill from evals
skillet tune <name> <skill>      # iteratively improve skill

Evals

Evals are stored in ~/.skillet/evals/<name>/:

# ~/.skillet/evals/conventional-comments/001.yaml
timestamp: 2025-01-15T10:30:00Z
name: conventional-comments
prompt: "Write a code review comment for..."
expected: "Should start with **issue** (blocking):"

Documentation

Full documentation available at the docs site:

Roadmap

See ROADMAP.md for future ideas and planned features.

License

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyskillet-0.2.7.tar.gz (319.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pyskillet-0.2.7-py3-none-any.whl (108.4 kB view details)

Uploaded Python 3

File details

Details for the file pyskillet-0.2.7.tar.gz.

File metadata

  • Download URL: pyskillet-0.2.7.tar.gz
  • Upload date:
  • Size: 319.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.9.26 {"installer":{"name":"uv","version":"0.9.26","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for pyskillet-0.2.7.tar.gz
Algorithm Hash digest
SHA256 7d49eee48954910771d0d037849dc9a30bca2d0a811f87165e6d0d72f810a29b
MD5 3698c456ee17b6edc81362d644fb9a1d
BLAKE2b-256 70b3a030dfb26e0bbecbe3e31cf3c6683fd64c3579b1ba6be7bdcaeb92d1fa00

See more details on using hashes here.

File details

Details for the file pyskillet-0.2.7-py3-none-any.whl.

File metadata

  • Download URL: pyskillet-0.2.7-py3-none-any.whl
  • Upload date:
  • Size: 108.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.9.26 {"installer":{"name":"uv","version":"0.9.26","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for pyskillet-0.2.7-py3-none-any.whl
Algorithm Hash digest
SHA256 e1eab0bac3c8b9441a793ad5aa324c220fdee40f60a926bff25d00dd2613ad67
MD5 ba5f8525a09bca81f7d6119e0bab3dd2
BLAKE2b-256 d80a8f22b951cba09283a35ddfbe6d71c0c7c4021abedc310b6504ea22cbe336

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page