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Category: Security & ComplianceNo API key required

Skill Evaluator

Evaluate Clawdbot skills for quality, reliability, and publish-readiness using a multi-framework rubric (ISO 25010, OpenSSF, Shneiderman, agent-specific heuristics). Use when asked to review, audit, evaluate, score, or assess a skill before publishing, or when checking skill quality. Runs automated structural checks and guides manual assessment across 25 criteria.

personAuthor: terwoxhubclawhub
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Skill Evaluator

Evaluate skills across 25 criteria using a hybrid automated + manual approach.

Quick Start

1. Run automated checks

python3 scripts/eval-skill.py /path/to/skill
python3 scripts/eval-skill.py /path/to/skill --json    # machine-readable
python3 scripts/eval-skill.py /path/to/skill --verbose  # show all details

Checks: file structure, frontmatter, description quality, script syntax, dependency audit, credential scan, env var documentation.

2. Manual assessment

Use the rubric at references/rubric.md to score 25 criteria across 8 categories (0–4 each, 100 total). Each criterion has concrete descriptions per score level.

3. Write the evaluation

Copy assets/EVAL-TEMPLATE.md to the skill directory as EVAL.md. Fill in automated results + manual scores.

Evaluation Process

  1. Run eval-skill.py — get the automated structural score
  2. Read the skill's SKILL.md — understand what it does
  3. Read/skim the scripts — assess code quality, error handling, testability
  4. Score each manual criterion using references/rubric.md — concrete criteria per level
  5. Prioritize findings as P0 (blocks publishing) / P1 (should fix) / P2 (nice to have)
  6. Write EVAL.md in the skill directory with scores + findings

Categories (8 categories, 25 criteria)

| # | Category | Source Framework | Criteria | |---|----------|-----------------|----------| | 1 | Functional Suitability | ISO 25010 | Completeness, Correctness, Appropriateness | | 2 | Reliability | ISO 25010 | Fault Tolerance, Error Reporting, Recoverability | | 3 | Performance / Context | ISO 25010 + Agent | Token Cost, Execution Efficiency | | 4 | Usability — AI Agent | Shneiderman, Gerhardt-Powals | Learnability, Consistency, Feedback, Error Prevention | | 5 | Usability — Human | Tognazzini, Norman | Discoverability, Forgiveness | | 6 | Security | ISO 25010 + OpenSSF | Credentials, Input Validation, Data Safety | | 7 | Maintainability | ISO 25010 | Modularity, Modifiability, Testability | | 8 | Agent-Specific | Novel | Trigger Precision, Progressive Disclosure, Composability, Idempotency, Escape Hatches |

Interpreting Scores

| Range | Verdict | Action | |-------|---------|--------| | 90–100 | Excellent | Publish confidently | | 80–89 | Good | Publishable, note known issues | | 70–79 | Acceptable | Fix P0s before publishing | | 60–69 | Needs Work | Fix P0+P1 before publishing | | <60 | Not Ready | Significant rework needed |

Deeper Security Scanning

This evaluator covers security basics (credentials, input validation, data safety) but for thorough security audits of skills under development, consider SkillLens (npx skilllens scan <path>). It checks for exfiltration, code execution, persistence, privilege bypass, and prompt injection — complementary to the quality focus here.

Dependencies

  • Python 3.6+ (for eval-skill.py)
  • PyYAML (pip install pyyaml) — for frontmatter parsing in automated checks