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Skill Benchmark

ASecurity

Benchmark AI skill effectiveness by measuring implementation quality against legacy constraints.

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  • Added June 6, 2026
developmentgobash

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A100/100

Scanned October 3, 2026

npx -y skills add HoangNguyen0403/agent-skills-standard --skill skill-benchmark --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
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=<feature>, ticket=<id/url>, mode=interactive|autonomous|channel, channel=<id>, auto_continue=true|false, profile=business|hybrid|technical.

## Instructions

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


# πŸ“Š Skill Benchmark Orchestrator

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

---

## Step 1 β€” Project Context & Active Skills

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

```bash
# 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
```

---

## Step 2 β€” Auto-Select a Legacy Trap

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

- πŸ”΄ **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).

---

## Step 3 β€” Build Eval-Driven Scorecard

Source your scorecard from `evals/evals.json`, not from hardcoded patterns.
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`.

---

## Step 4 β€” Benchmark Report & Compliance Delta

Output the scorecard and compliant score using the templates in `<SKILLS>/common/common-skill-creator/references/benchmark.md` when synced.

- **Compliance Score Before vs After**.
- **Ξ” Delta: +Z%** πŸš€.
- **Eval Alignment**: How well does the skill teach what the eval tests?
- **Behavior Coverage**: pressure scenarios, rationalizations, red flags, behavior assertions.

---

## Step 5 β€” Skill Applicability & Iteration

For every `❌ FAIL`, identify the root cause using the **Iteration Table** in:
`<SKILLS>/common/common-skill-creator/references/benchmark.md` when synced.

1. Signal not matching file? β†’ Refine trigger.
2. Rule too vague? β†’ Add Anti-Pattern rule.
3. Conflict? β†’ Ensure P0 overrides P1.
4. Guardrail weak under pressure? β†’ Add rationalization counters and red flags.

### Suggested .skillsrc Exclusions

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

```yaml
exclude:
  - [skill-id] # reason
```

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