rde-eval

GitHub

用于在本地对 React Doctor 规则变更进行定向评估,通过运行样本、检查命中结果并分类真假阳性,为 PR 合并提供验证证据。

.agents/skills/rde-eval/SKILL.md millionco/react-doctor

Trigger Scenarios

需要验证未提交的规则变更 审查规则评估的假阳性或真阳性 提交 PR 前的本地测试阶段

Install

npx skills add millionco/react-doctor --skill rde-eval -g -y
More Options

Non-standard path

npx skills add https://github.com/millionco/react-doctor/tree/main/.agents/skills/rde-eval -g -y

Use without installing

npx skills use millionco/react-doctor@rde-eval

指定 Agent (Claude Code)

npx skills add millionco/react-doctor --skill rde-eval -a claude-code -g -y

安装 repo 全部 skill

npx skills add millionco/react-doctor --all -g -y

预览 repo 内 skill

npx skills add millionco/react-doctor --list

SKILL.md

Frontmatter
{
    "name": "rde-eval",
    "description": "Run a targeted local React Doctor Evals loop against an uncommitted rule change. Use after focused rule tests pass, while inspecting real open-source hits, or when rule-validate needs local false-positive evidence before pull request parity."
}

Run a local rule evaluation

Use React Doctor Evals (RDE) for bounded local iteration. Use run-parity only after the change has a pushed pull request.

Prepare both checkouts

export REACT_DOCTOR_CHECKOUT=/absolute/path/to/react-doctor
export RDE_CHECKOUT=/absolute/path/to/react-doctor-evals

git -C "$RDE_CHECKOUT" pull --ff-only
ni -C "$RDE_CHECKOUT"
nr -C "$RDE_CHECKOUT" build
nr -C "$REACT_DOCTOR_CHECKOUT" build

The path: spec reads uncommitted React Doctor changes. Run RDE commands from the eval checkout.

Run a bounded sample

cd "$RDE_CHECKOUT"
node dist/cli.js run "path:$REACT_DOCTOR_CHECKOUT" --runner local --take 100
node dist/cli.js digest "path:$REACT_DOCTOR_CHECKOUT" --rule <rule-id>
node dist/cli.js digest "path:$REACT_DOCTOR_CHECKOUT" --json --rule <rule-id> > <artifact-directory>/hits.json

Increase --take only after tests and the first sample pass.

Inspect target-rule hits

For each hit, or a representative sample when counts are high:

  1. Open the pinned repository at the reported location.
  2. Compare the code with the rule contract.
  3. Classify the hit as true positive, false positive, or unsupported.
  4. Add a rule regression test for each false positive.
  5. Add confirmed false positives to the fuzz regression corpus.
  6. Rebuild and rerun the same sample.

Record repository count separately from project-root count. Do not treat error records as clean scans.

Report results

Report checkout revisions, target rule, repositories, project roots, diagnostics, inspected hits, fixed false positives, and the artifact path. State any setup error or skipped repository.

After local validation, return to rule-validate. That skill decides whether to invoke pull request parity.

Version History

  • 4fbab2d Current 2026-07-25 11:11

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2026-07-25 11:11

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