rule-research
Define a precise React Doctor rule contract before implementation. Use when validating a rule idea, collecting official or open-source evidence, identifying false-positive traps, choosing detector precision, or setting first-version boundaries.
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SKILL.md
---
name: rule-research
description: Define a precise React Doctor rule contract before implementation. Use when validating a rule idea, collecting official or open-source evidence, identifying false-positive traps, choosing detector precision, or setting first-version boundaries.
---
# Research a rule
Produce a rule contract that `rule-writing` can implement without guessing.
## Define the behavior
Resolve only questions that affect correctness:
- Which code pattern should report?
- Which runtime behavior makes it harmful?
- Which similar code must stay quiet?
- Does detection need syntax, scope, or path analysis?
- Which imported, dynamic, type-driven, or interprocedural cases stay out of scope?
If the user requested implementation, make the contract concise and continue.
## Collect evidence
1. Define the rule in one sentence: `This rule catches <pattern> that causes <problem>.`
2. Explain the runtime reason.
3. Inspect nearby rules, tests, utilities, and the generated registry.
4. Use `truffler` before proposing a new detector or helper:
```sh
bunx @rayhanadev/truffler "<symbol-or-behavior>" \
packages/oxlint-plugin-react-doctor/src/plugin \
--kind function,interface,type,constant --limit 20
```
5. Gather official documentation, implementation notes, related linter behavior, and open-source examples.
6. Separate strong positives, adjacent patterns, valid traps, and unsupported cases.
7. Choose syntax-only, scope-aware, or path-aware detection.
Use `rde-eval` when a bounded open-source sample could change the contract. Leave final pull request parity to `rule-validate`.
## Write the contract
Return:
```md
Rule definition:
<pattern and specific problem>
Runtime reason:
<short explanation>
Detector precision:
<syntax-only, scope-aware, or path-aware>
Evidence:
- <source and implication>
Strong positives:
- <reportable examples>
False-positive traps:
- <valid examples>
In scope:
- <supported cases>
Out of scope:
- <explicit boundaries>
Test seeds:
- <invalid and valid fixtures>
Open questions:
- <correctness blockers only>
```
Treat false positives as correctness bugs. Keep the diagnostic narrower than or equal to the proven behavior. Split adjacent ideas into separate rules.