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AC ty

Checks Python code for type errors with ty, Astral's fast type checker and language server written in Rust. Use when a user asks to type check a Python project, add ty to pyproject.toml or CI, silence or baseline existing type errors, set up a type-checking language server in VS Code, Neovim, Zed or PyCharm, or move from mypy or pyright. Covers ty check, configuration, rule levels, ignore comments and output formats.

TerminalSkills/skills Agent Skills author: TerminalSkills 2 files body ≈ 2 006 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Checks Python code for type errors with ty, Astral's fast type checker and language server written in Rust.

As a process C 58/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, progress reporting

ProcedureVS CodeGitHubSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
C
58/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note edit-residue the text marks something as outdated (lines 83, 153): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 58/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 100Steps. 17 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2006 tokens
    • 100Running it twice. No mutating operations

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +2Single-language instructions
    • +3Description length 420: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 17 items
    • +3Output format is stated explicitly
    • +4Has examples (12 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.