| name | skill-benchmark |
| description | Scores any SKILL.md across 5 quality dimensions, runs a compatibility check against 50+ AI agents, and returns a ranked fix list. Trigger when the user asks to benchmark, score, or audit a skill, wants to check cross-agent compatibility (Cursor, Windsurf, Gemini, etc.), needs a ranked fix list before publishing a SKILL.md to the community repo, is comparing two skills before a pull request, or wants to audit a SKILL.md for compatibility before opening a PR. |
Skill Benchmark
Reads a target SKILL.md, scores it across 5 weighted dimensions (100 pts
total), runs a static compatibility analysis against 50+ agent profiles, and
returns a structured report with a ranked fix list.
No agents need to be installed. Everything is static analysis — you read
the skill file, apply the rubric below, and produce the report.
Protocol
Step 0 — Locate the target skill
- If the user provided a path, read that file directly.
- If not, search in this priority order:
- Current directory:
SKILL.md, */SKILL.md
- Project skill paths:
.claude/skills/, .agents/skills/, .cline/skills/
- Global paths:
~/.claude/skills/, ~/.config/agents/skills/
- If multiple are found, list them and ask the user to confirm which one.
- If no SKILL.md is found after exhausting all search paths, stop and output:
[skill-benchmark error] No SKILL.md found — provide a file path to continue.
- Read the full file into context before proceeding.
Step 1 — Intake
Extract and note:
- Skill name (frontmatter
name: field)
- Description (frontmatter
description: field, full text)
- Body length (line count)
- Has bundled resources? (scripts/, references/, assets/ subdirs)
- Explicit agent targets (any
--agent flag mentions or agent-specific sections)
Step 2 — Score each dimension
Apply the rubric in references/rubric.md. For each dimension, note the
score, a one-sentence rationale, and the single most impactful fix.
| # | Dimension | Max pts |
|---|
| 1 | Trigger quality | 25 |
| 2 | Instruction clarity | 25 |
| 3 | Agent-agnostic design | 20 |
| 4 | Self-containment | 15 |
| 5 | Output definition | 15 |
| Total | 100 |
Scoring is strict. A score of 70+ means the skill is publishable. Below 50
means it will silently fail on most agents.
Step 3 — Run compatibility matrix
Read references/agent-profiles.md. For each of the 7 agent profiles,
check the target skill for the compatibility signals listed. Assign one of:
- ✅ Compatible — no blocking signals found
- ⚠️ Partial — one or more soft-fail signals (skill may work but
will degrade or skip steps)
- ❌ Likely broken — one or more hard-fail signals
Then map each named agent to its profile result. When an agent appears in
multiple profiles (e.g., Claude Code in A and C), assign the worst result
across all applicable profiles: ❌ overrides ⚠️ overrides ✅.
Step 4 — Generate the report
Use the template in references/report-template.md.
Fill in every section. Do not skip the "Top fixes" section — it is the
most actionable part and the reason the skill exists.
Sort the 54 agents into three groups (Compatible / Partial / Broken) and
list them comma-separated. Do not list each agent on its own line.
Step 5 — Offer next steps
After presenting the report, offer exactly these three options:
- Auto-fix — apply the top-ranked fix and re-score immediately
- Deep dive — expand any dimension score with full evidence from the skill text
- Export — save the report as
skill-benchmark-report.md in the same directory as the evaluated skill
