Individual skill
evals
Build a regression + eval harness for AI-written code and AI features. Generates characterization tests that lock current behavior before a refactor, scaffolds a Promptfoo eval suite for chatbots/RAG/classifiers, and wires it into the ship-gate. Use when the user wants evals, regression tests for AI code, to stop AI features drifting, or to test an LLM feature.
skills/evals/SKILL.md
Source commit ed232cba00040a3a8294aff08d14a0053cb8a0ae
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Network or broad shell
- Last checked
- Nov 11, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 123
- Repository last updated
- Jul 8, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- ai Repository topic
- claude Repository topic
- claude-code Repository topic
- claude-code-plugin Repository topic
- code-review Repository topic
- developer-tools Repository topic
- indie-hackers Repository topic
- lighthouse Repository topic
- performance Repository topic
- playwright Repository topic
- engineering Derived category
- testing Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Read excerpt
# Evals — Regression Harness for AI Code & AI Features
The defining 2026 problem: AI-written code passes review but **fails at runtime** (New Relic: 82% of teams had an AI-code production failure), and AI *features* (chatbots, RAG, classifiers) drift silently as prompts and models change. The fix the industry converged on: **the regression suite becomes the primary reviewer.** This skill builds that suite.
Two complementary layers:
- **Characterization tests** — lock the *current* behavior of code before an agent refactors it, so a regression is caught immediately.
- **LLM-feature evals** — assert that each AI feature still does its job (stays on-topic, no PII leak, correct format, acceptable latency/cost) on every change.
## Process
### Phase 1: Locate what needs evals
```bash
node ${CLAUDE_PLUGIN_ROOT}/tools/eval-scanner.mjs <project-directory>