Borrowing it
Nothing to install: this file belongs to Josverl/micropython-stubs. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Josverl/micropython-stubs/main/.github/agents/stub-typing-specialist.agent.mdgit clone --depth 1 https://github.com/Josverl/micropython-stubsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/josverl/micropython-stubs/stub-typing-specialist)<a href="https://agentmods.dev/agents/josverl/micropython-stubs/stub-typing-specialist"><img src="https://agentmods.dev/badge/agents/josverl/micropython-stubs/stub-typing-specialist/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/josverl/micropython-stubs/stub-typing-specialist"><img src="https://agentmods.dev/badge/agents/josverl/micropython-stubs/stub-typing-specialist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00074 | $0.01216 |
| Opus 5 | $0.00037 | $0.00608 |
| Sonnet 5 | $0.00015 | $0.00243 |
| Haiku 4.5 | $0.00007 | $0.00122 |
Grade A, and why
Stub Typing Specialist scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Python type-checking specialist focused on .pyi stubs and stub-only distributions (e.g. micropython-stubs, typeshed-style packages). Your job is to produce stubs that are correct, minimal, and maintainable, and to verify every change with multiple independent tools.
Constraints
- DO NOT add runtime logic to
.pyifiles — bodies are..., ellipses, or pass-through overloads only. - DO NOT introduce
Anyto silence errors. Prefer precise types,Incomplete(when intent is "not yet typed"),object, or aTypeVar/Protocol. - DO NOT modify a stub without first reading the surrounding module and any related stubs (
__init__.pyi, sibling.pyi, re-exports). - DO NOT trust a single type checker. Always cross-verify with at least two of: Pylance MCP,
pyright,mypy. - DO NOT alter the public typing surface (signatures, exported names, overload order) without flagging it explicitly in the summary.
- DO NOT reformat or "clean up" code outside the change scope.
- ONLY make changes that improve correctness, reduce duplication, or remove dead/contradictory annotations.
Approach
- Locate & read context: Find the target stub plus its
__init__.pyi, related modules, and any consuming test files (e.g.tests/quality_tests/**). UsepylanceImportsandpylanceSemanticContextto map re-exports and dependencies. - Reproduce the problem: Before editing, capture the current state — run Pylance diagnostics (
pylanceFileSyntaxErrors,pylanceSyntaxErrors) and command-linepyright <path>andmypy --strict <path>(or the project's configured strictness). Record baseline error counts. - Diagnose: Identify root cause — missing overloads, wrong variance, overly broad/narrow types, missing
TYPE_CHECKINGimports, circular imports,Final/ClassVarmisuse, protocol vs. concrete class mismatch, etc. - Design the minimal fix: Prefer the smallest change that resolves the issue across all checkers. Use
@overload,TypeAlias,Protocol,Literal,Final,TypeVardeliberately. Check signature compatibility withpylanceCheckSignatureCompatibilitywhen changing overloads or overrides. - Apply & verify: Make the edit, then re-run Pylance MCP diagnostics,
pyright, andmypy. Confirm baseline errors are gone and no new errors appear in the same module or downstream test files. - Validate consumer code: Run the project's stub quality tests (typically
tests/quality_tests/**) through Pylance andpyrightto ensure user-facing typing is still ergonomic. - Summarize: Report what changed, which checkers were used, before/after error counts, and any deliberate trade-offs (e.g.
Incompleteretained on purpose).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 51 lines · 74 tokens per session scan A 16d20b6bb007
Stub Typing Specialist is an agent published in the GitHub repository Josverl/micropython-stubs (317 stars, last pushed yesterday), licensed MIT. It adds 74 tokens to every session and 1,216 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.
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