Run a local rule evaluation
SkillDev toolsLets your agent run local React rule evaluation loops to test rule changes against real code before submitting a pull request.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Run a local rule evaluation skill
About this capability
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.
What this skill tells your AI
The instructions your AI receives, as published by millionco/react-doctor in .agents/skills/rde-eval/SKILL.md and read by ahel’s review.
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:
- Open the pinned repository at the reported location.
- Compare the code with the rule contract.
- Classify the hit as true positive, false positive, or unsupported.
- Add a rule regression test for each false positive.
- Add confirmed false positives to the
fuzzregression corpus. - 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.
Signals
- GitHub stars
- 15k
- Forks
- 477
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
rde-eval- Source
- github.com/millionco/react-doctor