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rde-eval

rde-eval

github.com/millioncoTesting & quality15.1k327 installsUpdated 2w ago
Repository

About rde-eval

rde-eval is a skill for running bounded local evaluations with React Doctor Evals against React Doctor changes. It guides setup, sampled runs, rule-hit inspection, regression testing, and result reporting.

Key features

  1. 01Prepares React Doctor and RDE checkouts
  2. 02Runs local evaluations on a bounded sample
  3. 03Digests results by rule
  4. 04Classifies and investigates rule hits
  5. 05Adds false positives to regression tests
  6. 06Reports evaluation details and artifacts

Use cases

  1. 01Testing an uncommitted React Doctor change locally
  2. 02Investigating a rule's hits across sampled repositories
  3. 03Verifying false-positive fixes with a repeat run

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/millionco/react-doctor --skill rde-eval

After installing, type/rde-evalin Claude Code to confirm it loaded.

Details

From the project README

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.

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