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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Claude skills I'm experimenting with. Please review carefully before use.
| Date | Stars |
|---|---|
| 2026-07-31 | 266 |
| 2026-08-06 | 266 |
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# claude-skills Reusable [Claude Code](https://docs.anthropic.com/en/docs/claude-code) slash command skills. To install a skill, copy it to `~/.claude/commands/` (rename from `.md.txt` to `.md`). The skills and parts of the project documentation were produced semi-automatically using Claude Code. You can read more about the general thinking behind these skills on [my blog](https://honnibal.dev). ## Skills All skills accept an optional argument to scope the work to specific files or directories. If no argument is given, they work through the project or ask you to choose a starting scope. The skills are set to `disable-model-invocation: true` by default. This means installing them shouldn't pollute your context. You can change this if you want the model to invoke them automatically. ### `tighten-types.md.txt` Systematically review Python source files and tighten type annotations. Works through a prioritised checklist: missing class attribute annotations, vague `Any` types replaced with concrete library types, structured dicts promoted to Pydantic models or `TypedDict`, `@overload` signatures for narrowable unions, redundant in-body annotations fixed at the root cause, and style modernisation (`Optional[X]` → `X | None`, etc.). ``` /tighten-types src/mypackage/core.py ``` ### `contract-docstrings.md.txt` Write docstrings that document each function's **contract** --- what it requires of callers, what it guarantees, and how it fails. Analyses four dimensions: input invariants (preconditions beyond the type signature), errors raised on violation (explicit checks vs. implicit crashes vs. silent wrong results), errors from external state (filesystem, network, databases), and silenced errors (broad `except` blocks, `.get()` defaults, `suppress()`). Produces a structured `Contract:` section with `Preconditions:`, `Raises:`, and `Silences:` subsections. ``` /contract-docstrings src/mypackage/pipeline.py ``` ### `hypothesis-tests.md.txt` Generate property-based tests using [Hypothesis](https://hypothesis.readthedocs.io/). Reads production code, designs input strategies in `tests/strategies.py` that model the valid search-space for each function (encoding constraints rather than filtering), then writes minimal, behaviour-focused tests. Tests target core contracts --- roundtrips, idempotence, invariant preservation, equivalence to reference implementations --- rather than structural trivia or reimplementations of the function under test. ``` /hypothesis-tests src/mypackage/scoring.py ``` ### `mutation-testing.md.txt` Assess test suite strength by introducing deliberate bugs (mutations) one at a time and checking whether any test catches each one. Mutations are chosen from a catalogue (delete side effects, negate conditions, change boundaries, hardcode returns, remove guards, swap operators, modify defaults, swap argument order). Each mutation is applied, tests are run, and the mutation is reverted. Produces a summary table with mutation score, uncaught gaps, diagnostic quality ratings, and recommended tests. Optionally implements missing tests for survived mutations. ``` /mutation-testing src/mypackage/ ``` ### `pre-mortem.md.txt` Imagine future bug post-mortems for the codebase. Reads production code and identifies fragile areas --- implicit ordering dependencies, shared mutable state, stringly-typed contracts, baked-in data assumptions, coincidental correctness, non-atomic operations, invisible invariants, load-bearing defaults, implicit resource lifecycles, and version-coupled assumptions. Writes realistic incident reports (severity, cause, why it broke, how it was caught, hardening suggestions) for bugs that haven't happened yet but plausibly could from reasonable future edits. Outputs a `PRE-MORTEM.md` report. ``` /pre-mortem src/mypackage/ ``` ### `stub-package.md.txt` Generate a condensed structural overview of a Python package or module --- signatures, imports, class attributes, and docstrings only, with funct
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:597b98ab4922608a, llm:Repository description: "Claude skills I'm experimenting with. Please review carefully before use." Language: Python. Implies collection of skills/agents/integrations for Claude (AI assistant).
matched fp:597b98ab4922608a, llm:Repository description: "Claude skills I'm experimenting with. Please review carefully before use." Language: Python. Implies collection of skills/agents/integrations for Claude (AI assistant).
matched fp:597b98ab4922608a, llm:Repository description: "Claude skills I'm experimenting with. Please review carefully before use." Language: Python. Implies collection of skills/agents/integrations for Claude (AI assistant).