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name: skill-benchmark description: "Benchmark AI skill effectiveness by measuring implementation quality against legacy constraints." metadata: internal: true triggers: keywords: - skill benchmark - workflow

Skill Benchmark Skill

[!IMPORTANT] Benchmark AI skill effectiveness by measuring implementation quality against legacy constraints.

Optional args: slug=, ticket=<id/url>, mode=interactive|autonomous|channel, channel=, auto_continue=true|false, profile=business|hybrid|technical.

Instructions

When the user asks to perform this workflow, execute the following steps:

📊 Skill Benchmark Orchestrator

Goal: Quantify how much active skills improve implementation quality. Deliver a prioritized compliance delta and skill applicability report.

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Step 1 — Project Context & Active Skills

Identify the tech stack and all active skills in AGENTS.md.

# 1. Total source files and lines changed
find src -name "*.ts" -o -name "*.tsx" | xargs wc -l 2>/dev/null | sort -rn | head -20
# 2. Check active skill registry
cat AGENTS.md | head -80

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Step 2 — Auto-Select a Legacy Trap

Pick the file automatically. Rank candidates by the severity of anti-patterns:

• 🔴 P0: Hardcoded secrets; Logic inside UI components.
• 🟠 P1: Wrong Router pattern; Global state for local concerns; Missing design tokens.
• 🟡 P2: Raw user-facing strings (i18n).

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Step 3 — Build Eval-Driven Scorecard

Source scorecard from evals/evals.json. Distinguish structural checks, textual transcript assertions, and executable verifier outcomes. Never add canned assertion keywords to skills to artificially inflate scores (no answer-anchor padding). Follow the Scorecard Rubric in <SKILLS>/common/common-skill-creator/references/benchmark.md when synced:

1. Read <SKILLS>/<category>/<skill>/evals/evals.json.
2. Generate columns for Failure Pattern and Success Pattern.
3. Refactor the file, citing the exact skill rule for each change.
4. For guardrail skills, read pressure_scenarios, rationalizations, red_flags, and behavior_assertions.

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Step 4 — Benchmark Report & Evidence Breakdown

Output scorecard and evidence breakdown using templates in <SKILLS>/common/common-skill-creator/references/benchmark.md when synced.

• Score Before vs After: Report structural, textual transcript, and executable pass rates separately.
• Evidence Type: Explicitly label transcript text matches vs deterministic executable outcomes.
• Behavior Coverage: Pressure scenarios, rationalizations, red flags, behavior assertions.

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Step 5 — Skill Applicability, Ablation & Iteration

For every failure or candidate rule, evaluate using the Iteration Table and ablation criteria in benchmark.md:

1. Signal not matching file? → Refine trigger.
2. Rule ineffective? → Clarify procedural logic; do not pad canned keywords.
3. Conflict? → Ensure P0 overrides P1.
4. Baseline model passes or repeated ablation shows zero delta? → Flag as retirement candidate; preserve safety controls until deterministic enforcement exists.

Suggested .skillsrc Exclusions

Recommend any skills that are noisy or non-applicable for the project.

exclude:
  - [skill-id] # reason