agentskill-kit is a command line toolkit for agent skills, the SKILL.md folders that coding agents such as
Claude Code, Cursor, Codex, Gemini CLI and Hermes load when a task matches. It checks a skill before you trust it,
generates new ones, and installs the same skill into every agent you use.
- Lint a skill: name, description, structure. Works offline.
- Scan it for prompt injection, hidden unicode, secrets and dangerous commands.
- Test it: run the tests that ship with the skill in an isolated folder.
- Forge a new skill from a task description with any model, including free and local ones.
- Mine your shell history for routines that should be skills.
- Export one skill to Claude Code, Cursor, Windsurf, Copilot, Codex and Gemini CLI.
- Share skills through a static registry with checksums and a searchable website.
No runtime dependencies. No paid service required. Python 3.9 or newer on Linux, macOS and Windows.
Install
pip install agentskill-toolkit
The PyPI package is named agentskill-toolkit (the shorter name was not available). It installs the askit command and the longer alias agentskill. The repository, the Python module (agentskill_kit) and the commands keep the agentskill-kit name.
Quick start
Check a skill without any API key:
askit lint skills/my-skill
askit scan skills/my-skill
askit test skills/my-skill
askit score skills/my-skill
Create one with a free model (a local Ollama model, or a Groq or Gemini key on the free tier):
askit forge --task "turn meeting notes into action items with owners and due dates"
Use it in your agents:
askit export skills/meeting-notes-to-actions --target claude
askit export skills/meeting-notes-to-actions --target cursor
askit export skills/meeting-notes-to-actions --target all
Install something from the community registry:
askit search docker
askit install dockerfile-linter
Try everything offline with the built-in demo model: askit forge --task "anything" --provider mock.
Why this exists
Skills are plain text that an agent obeys, so they deserve the same care as code you run: a review, a linter, a test and a look at what they do. At the same time every agent wants a slightly different file layout, and writing good skills by hand is slow. agentskill-kit covers both: quality gates for skills, and tools that do the tedious parts.
Commands
| Command | What it does |
|---|---|
askit init NAME |
Create a skill from a template, optionally with a script and tests |
askit lint [PATH] |
Check SKILL.md structure (--strict, --format json|github) |
askit scan [PATH] |
Security scan (--fail-on high|medium|low|never) |
askit test [PATH] |
Run tests/cases.json and tests/test_*.py of each skill |
askit score [PATH] |
Combine lint, scan and tests into one score and a pass or fail gate |
askit forge |
Generate a skill with a model, verify it and refine it until it passes |
askit eval PATH |
Check how well a model follows a skill, with an optional baseline run |
askit mine |
Find repeated workflows in shell history and draft skills |
askit export PATH |
Convert and install a skill for another agent |
askit search, install, uninstall, list |
Work with the registry, GitHub folders and local folders |
askit pack, publish |
Bundle a skill, run the quality gate, prepare a pull request |
askit registry build|site |
Build a registry index or a static website |
askit serve |
Browse the skills on your machine in a local web page |
askit providers, config, doctor |
Models, settings and environment checks |
Every command has --help. Add --lang tr for a Turkish interface.
Free first, paid optional
| Provider | Cost | How |
|---|---|---|
| Ollama, LM Studio | free, local | run a local model, no key |
| Groq | free tier | GROQ_API_KEY |
| Google Gemini | free tier | GEMINI_API_KEY |
| OpenRouter | free models | OPENROUTER_API_KEY, pick a :free model |
| Any OpenAI compatible server | yours | ASKIT_BASE_URL, ASKIT_MODEL |
| OpenAI, Anthropic | paid, optional | OPENAI_API_KEY, ANTHROPIC_API_KEY |
askit providers shows what is ready. Details in docs/providers.md.
forge does not rely on tool calling. The loop is controlled by code, so small local models work. The model only
writes files; lint, scan and tests decide whether they are good enough.
How forge decides
task or notes
|
v
model drafts SKILL.md, scripts and tests/cases.json
|
v
lint + scan + run tests in a clean folder -> score
| |
| below threshold: failures go back | at or above threshold,
| to the model (up to 3 rounds) | no high findings
v v
best attempt kept written to skills/<name>/
The score is not the model's opinion. It comes from real checks.
Nothing is written when the best attempt misses the threshold, unless you pass --force.
Mine your history
$ askit mine --file examples/shell-history-sample.txt
-- read 20 commands
Found 1 repeated workflow(s)
#1 git-status-add-commit (4x)
git status
git add -A
git commit -m <str>
git push origin main
$ askit mine --file examples/shell-history-sample.txt --draft 1
Secrets are masked before anything is shown. See docs/mining.md.
Export targets
| Target | Result |
|---|---|
claude |
.claude/skills/<name>/ or ~/.claude/skills/ with --global |
hermes |
.hermes/skills/<name>/ or ~/.hermes/skills/ |
cursor |
.cursor/rules/<name>.mdc |
windsurf |
.windsurf/rules/<name>.md |
copilot |
.github/instructions/<name>.instructions.md |
codex |
managed block in AGENTS.md |
gemini |
managed block in GEMINI.md |
Exports are repeatable: managed blocks are replaced, not duplicated. More in docs/export-targets.md.
Starter skills
The registry ships 16 skills that pass every check. Nine of them include scripts with tests, so you can read how a tested skill is built.
| Skill | What it does |
|---|---|
log-analyzer |
severity counts, time range and frequent errors of a log |
python-code-smells |
bare except, mutable defaults, missing docstrings and long functions |
csv-profiler |
column types, missing values and ranges for a CSV |
json-diff |
structural diff of two JSON files |
dockerfile-linter |
unpinned images, root user, ADD vs COPY, secrets in ENV |
env-file-auditor |
.env against .env.example, without printing values |
todo-extractor |
TODO, FIXME and HACK inventory of a source tree |
changelog-generator |
conventional commits to grouped release notes |
api-endpoint-tester |
smoke test an API from a JSON file |
commit-message-writer |
clear conventional commit messages |
pr-description-writer |
pull request descriptions reviewers can use |
sql-query-reviewer |
safety, correctness and performance review of SQL |
meeting-notes-to-actions |
decisions, owners and open questions from notes |
readme-doctor |
what to fix in a README to get people to try a project |
secure-code-review |
a security checklist with a report format |
skill-author |
how to write a skill that triggers and works |
Browse them on the registry website, or run askit search and askit install NAME.
Use it in CI
- uses: Lethe044/agentskill-kit@main
with:
path: skills
strict: "true"
scan-fail-on: medium
Also available as a pre-commit hook. See docs/github-action.md.
Use it from Python
from agentskill_kit.lint import lint_skill
from agentskill_kit.scan import scan_skill
from agentskill_kit.scoring import evaluate_skill
quality = evaluate_skill("skills/log-analyzer")
print(quality.score, quality.grade, quality.passes_gate)
for issue in lint_skill("skills/log-analyzer").issues:
print(issue.code, issue.message)
print(scan_skill("skills/log-analyzer").verdict)
Security notes
- The scanner is a heuristic filter, not a guarantee. Read skills from sources you do not trust.
askit testisolates the working directory and environment and limits time and memory, but it is not a sandbox. Use a container for untrusted skills.- Registry downloads are verified against checksums, linted and scanned before installation.
Details in docs/security.md and SECURITY.md.
Hermes Agent
This project began as a Hermes Agent hackathon prototype. Hermes remains a first class target
(askit export --target hermes) and integrations/hermes/ holds the skill-forge playbook and an Atropos
training environment whose reward can use verified scores. See integrations/hermes.
Documentation
- Getting started
- Skill format, tests and scoring
- Providers
- Security model
- Export targets
- Registry and publishing
- Mining shell history
- GitHub Action and pre-commit
Roadmap
- More scanner rules and a community rule pack.
- Translated rule messages (the interface is already available in Turkish and English).
askit evalwith a judge model for open ended checks.- Skill dependencies and version constraints in the registry.
- Export targets for more agents.
Ideas and pull requests are welcome. See CONTRIBUTING.md for how to add a skill in a few minutes.
License
Metadata
Release files for agentskill-toolkit 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| agentskill_toolkit-0.1.0.tar.gz | 92.7 kB | With provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| agentskill_toolkit-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 173.3 kB
Release files / agentskill_toolkit-0.1.0.tar.gz
| Download URL | agentskill_toolkit-0.1.0.tar.gz |
|---|---|
| Size | 92.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
4be5b6798d14bc0a029c23c547d83f5f02f58ddfb573f2bb1cd6319bafc84655
|
|
BLAKE2b-256 checksum How to use checksums |
0e51e871978515bf4d66141373bac8deddd751787d45012095e8a7b3f505c6ce
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.16
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 26, 2026.
Transparency logRelease files / agentskill_toolkit-0.1.0-py3-none-any.whl
| Download URL | agentskill_toolkit-0.1.0-py3-none-any.whl |
|---|---|
| Size | 80.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
160c88421267338513676fd5bcce3ab3f158df28901fd64e6e52c018daa1b36b
|
|
BLAKE2b-256 checksum How to use checksums |
2287ee1f156662b481b05ff1ef05dff7d14c97e1df6c1de772580a418c27d608
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.16
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 26, 2026.
Transparency logSecurity for agentskill-toolkit 0.1.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
Full provenance
All 2 files in this release have been uploaded with provenance metadata.
Attestation for agentskill_toolkit-0.1.0.tar.gz
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 26, 2026.
Transparency logA note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.