Axiomata Skill Evaluator En

Axiomata Skill Evaluator — Universal OpenClaw Agent Skill Quality System. Dual evaluation: (1) Axioma 5-Dimension Framework (Structure 20%, Clarity 20%, Completeness 20%, Consistency 20%, Functionality 20%, 100pts total), (2) ISO 25010 Structural Framework (13 automated checks, 100% target). Self-contained: bundles evaluator.py (Axioma 5-Dim) and eval-skill.py (ISO 25010). Use when: evaluating a skill before publishing, improving a skill based on evaluation results, checking skill quality with automated analysis, auditing skill quality, or verifying a skill meets production standards.

Kofna3369@kofna3369

Install

openclaw skills install @kofna3369/axiomata-skill-evaluator-en

Axiomata Skill Evaluator v3.0

Universal, impersonal skill quality evaluator for OpenClaw agents.

Info	Value
Version	3.0.0
Type	Self-contained evaluation system
Evaluation	Dual (Axioma 5-Dim + ISO 25010)
Target	70+ (Axioma), 90%+ (ISO 25010)

1. Purpose and Scope

Objective

Provide complete skill quality evaluation using dual evaluation system:

Axioma 5-Dimension Framework (100 points)
ISO 25010 Structural Framework (13 automated checks)

Design Principles

text

SELF-CONTAINED + UNIVERSAL + IMPERSONAL

Principle	Description
Self-contained	All tools bundled in skill directory
Universal	Works for any OpenClaw agent
Impersonal	No agent-specific references

When to Use

Trigger	Action
Evaluate skill	Run dual evaluation
Pre-publish check	Run full evaluation pipeline
Improve skill	Analyze report and fix issues
Skill audit	Run complete audit
Check quality	Run automated checks

2. Dual Evaluation System

text

╔═══════════════════════════════════════════════════════════╗
║              DUAL EVALUATION ARCHITECTURE                ║
╠═══════════════════════════════════════════════════════════╣
║                                                           ║
║  ┌─────────────────────────────────────────────────┐      ║
║  │  1. Axioma 5-Dim Evaluation (100 pts)          │      ║
║  │                                                 │      ║
║  │  Dimensions:                                     │      ║
║  │  ├─ Structure     → 20%                         │      ║
║  │  ├─ Clarity      → 20%                         │      ║
║  │  ├─ Completeness → 20%                         │      ║
║  │  ├─ Consistency  → 20%                         │      ║
║  │  └─ Functionality → 20%                        │      ║
║  │                                                 │      ║
║  │  Target: 70+ score                             │      ║
║  └─────────────────────────────────────────────────┘      ║
║                        ↓                                ║
║  ┌─────────────────────────────────────────────────┐      ║
║  │  2. ISO 25010 Structural (13 checks)          │      ║
║  │                                                 │      ║
║  │  Categories: 8 categories, 25 standards       │      ║
║  │  Automated checks: 13 tests                    │      ║
║  │                                                 │      ║
║  │  Target: 90%+ (12/13 checks passing)          │      ║
║  └─────────────────────────────────────────────────┘      ║
║                                                           ║
╚═══════════════════════════════════════════════════════════╝

Evaluation Flow

text

[INPUT] Skill to evaluate
          ↓
 Phase 1: Axioma 5-Dim Evaluation
          ↓
 Phase 2: ISO 25010 Structural Checks
          ↓
 [OUTPUT] Quality report + recommendations

3. Bundled Tools

File	System	Purpose
`evaluator.py`	Axioma 5-Dim	5-dimension evaluation, bundled
`eval-skill.py`	ISO 25010	Automated structural checks, bundled

Tool Paths

bash

EVAL_PATH="<skill-directory>/scripts/"
SKILL_PATH="<skill-to-evaluate>"

# Axioma 5-Dim evaluation
python3 ${EVAL_PATH}evaluator.py <SKILL_PATH> --verbose

# ISO 25010 checks
python3 ${EVAL_PATH}eval-skill.py <SKILL_PATH> --verbose

4. Axioma 5-Dimension Evaluation

4.1 Dimension Breakdown

Dimension	Max	Target	What it checks
Structure	20	14+	Header, sections, formatting, metadata
Clarity	20	14+	Description, commands, examples, constraints
Completeness	20	14+	Tools, prerequisites, errors, edge cases
Consistency	20	14+	Naming, format, structure, style
Functionality	20	14+	Valid commands, documented outputs

4.2 Score Thresholds

Score	Status	Action
90-100	EXCELLENT	Ready for production
70-89	GOOD	Minor improvements possible
50-69	NEEDS_WORK	Major improvements needed
<50	POOR	Significant rewrite required

5. ISO 25010 Structural Checks

5.1 Automated Checks (13 total)

Category	Checks	What it verifies
Structure	6	Frontmatter, header, sections, formatting
Trigger	2	Description length, trigger contexts
Documentation	3	Body length, references, linked docs
Scripts	2	Python parse, no external deps

5.2 Pass Threshold

Result	Meaning
13/13	Perfect structural score
11-12/13	Acceptable, minor warnings
<11/13	Needs structural improvement

6. Command Reference

6.1 Axioma 5-Dim Evaluation

bash

# Basic evaluation
python3 <skill-directory>/scripts/evaluator.py <skill-path>

# Verbose output
python3 <skill-directory>/scripts/evaluator.py <skill-path> --verbose

# With auto-improvement suggestions
python3 <skill-directory>/scripts/evaluator.py <skill-path> --verbose --improve

# JSON output
python3 <skill-directory>/scripts/evaluator.py <skill-path> --json

6.2 ISO 25010 Checks

bash

# Basic ISO check
python3 <skill-directory>/scripts/eval-skill.py <skill-path>

# Verbose output
python3 <skill-directory>/scripts/eval-skill.py <skill-path> --verbose

# JSON output
python3 <skill-directory>/scripts/eval-skill.py <skill-path> --json

6.3 Evaluate All Skills

bash

# Evaluate all skills in parent directory
python3 <skill-directory>/scripts/evaluator.py --all

# Verbose all
python3 <skill-directory>/scripts/evaluator.py --all --verbose

7. Output Formats

7.1 Console Output

text

=== EVALUATION RESULTS ===
STRUCTURE       20/20 ████████████████████ 100%
CLARITY         17/20 █████████████████░░░ 85%
COMPLETENESS    14/20 ████████████░░░░░░░░ 70%
CONSISTENCY     10/20 ██████████░░░░░░░░░ 50%
FUNCTIONALITY   12/20 ████████████░░░░░░░░ 60%
------------------------------------------------------------
STATUS: GOOD (score 73%)

7.2 JSON Output

json

{
  "skill": "example-skill",
  "scores": {
    "structure": 20,
    "clarity": 17,
    "completeness": 14,
    "consistency": 10,
    "functionality": 12
  },
  "total": 73,
  "max": 100,
  "passed": true,
  "recommendations": [
    "[CONSISTENCY] Low score (50%)",
    "  -> Style: 2/5"
  ]
}

8. Examples

Example 1: Basic Evaluation

bash

$ python3 evaluator.py /path/to/skill --verbose
Read /path/to/skill/SKILL.md (2048 chars)
Structure: 20/20
Clarity: 17/20
Completeness: 14/20
Consistency: 10/20
Functionality: 12/20
============================================================
STATUS: GOOD (score 73%)

Example 2: ISO 25010 Check

bash

$ python3 eval-skill.py /path/to/skill --verbose
[STRUCTURE]
    Pass: 5/6
[TRIGGER]
    Pass: 2/2
[DOCUMENTATION]
    Pass: 2/3
[SCRIPTS]
    Pass: 2/2
[SECURITY]
    Pass: 2/2
==================================================
  Pass: 13  Warn: 0  Fail: 0
  Structural score: 100% (13/13 checks passed)

Example 3: JSON Output

bash

$ python3 evaluator.py /path/to/skill --json
{
  "skill": "example-skill",
  "scores": {
    "structure": 20,
    "clarity": 17,
    "completeness": 14,
    "consistency": 10,
    "functionality": 12
  },
  "total": 73,
  "max": 100,
  "passed": true,
  "recommendations": []
}

9. Self-Evaluation

The skill evaluates itself automatically:

bash

# Self-evaluation (when no path given, evaluates own directory)
python3 evaluator.py

# Expected output for v3.0:
# Score: 85+/100
# Status: GOOD to EXCELLENT

10. Recommendations Format

When a dimension scores below 70%:

text

[{DIMENSION}] Low score ({percentage}%)
  -> {specific issue}
  -> {specific issue}

Example:

text

[CONSISTENCY] Low score (50%)
  -> Cluster alignment partial: 2
  -> Style: 2/5

11. Constraints

Constraint	Description	Priority
70% minimum	Skills must score 70+ on Axioma 5-Dim	HIGH
90%+ structural	Target 90%+ on ISO 25010 checks	HIGH
Self-contained	All tools bundled, no external deps	HIGH
Impersonal	No agent-specific references	HIGH

Quality Thresholds

System	Minimum	Target
Axioma 5-Dim	70/100	90/100
ISO 25010	11/13	13/13
Structure	14/20	18/20
Clarity	14/20	18/20
Completeness	14/20	18/20
Consistency	14/20	18/20
Functionality	14/20	18/20

12. Error Handling

Error	Cause	Solution
SKILL.md not found	Missing file	Create SKILL.md first
Parse error	Corrupt file	Check file encoding
Module not found	Missing dependencies	Use bundled tools only

13. Workflow Integration

text

╔═══════════════════════════════════════════════════════════╗
║         SKILL PUBLISHING WORKFLOW                        ║
╠═══════════════════════════════════════════════════════════╣
║                                                           ║
║  1. Create Skill                                          ║
║      ↓                                                    ║
║  2. Self-Evaluate                                         ║
║      ↓ 70+ → Continue                                    ║
║  3. ISO 25010 Check                                      ║
║      ↓ 90%+ → Continue                                   ║
║  4. Fix Issues if Needed                                 ║
║      ↓                                                    ║
║  5. Publish to ClawHub                                   ║
║                                                           ║
║  RESULT: QUALITY SKILLS FOR PRODUCTION                   ║
║                                                           ║
╚═══════════════════════════════════════════════════════════╝

In Altum Per Qualitatem. 🧪 AXIOMATA SKILL EVALUATOR v3.0 — UNIVERSAL QUALITY SYSTEM