millionco/react-doctor

rde-eval

Run a targeted local React Doctor Evals loop against an uncommitted rule change.

Ver código-fonte

Como usar

  1. Copie o comando e verifique o pacote antes de instalar no seu ambiente de agente.
  2. Consulte no original as ferramentas, credenciais e ambientes necessários.
  3. Descreva os dados de entrada e a entrega esperada; confira a saída com as fontes.
npx skills add https://github.com/millionco/react-doctor --skill rde-eval

Antes de começar

  • A instalação não inclui assinatura de modelo, franquia API ou acesso aos seus arquivos.
  • Estrelas e instalações indicam atividade, não um teste independente de qualidade ou segurança.
Documento original do Skill

Renderizado do repositório de origem, preservando títulos, exemplos, código, tabelas, links e imagens.

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

sh
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

sh
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.

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