Dual Axis Skill Reviewer

reports/

• Random or fixed skill selection
• Auto-axis scoring with optional test execution
• LLM prompt generation
• LLM JSON review merge with weighted final score
• Cross-project review via

  --project-root

When to Use

• Need reproducible scoring for one skill in

  skills/*/SKILL.md

  .
• Need improvement items when final score is below 90.
• Need both deterministic checks and qualitative LLM code/content review.
• Need to review skills in a different project from the command line.

Prerequisites

• Python 3.9+

• uv

  (recommended — auto-resolves

  pyyaml

  dependency via inline metadata)
• For tests:

  uv sync --extra dev

  or equivalent in the target project
• For LLM-axis merge: JSON file that follows the LLM review schema (see Resources)

Workflow

• Same project:

  skills/dual-axis-skill-reviewer/scripts/run_dual_axis_review.py

• Global install:

  ~/.claude/skills/dual-axis-skill-reviewer/scripts/run_dual_axis_review.py

REVIEWER

# If reviewing from the same project:
REVIEWER=skills/dual-axis-skill-reviewer/scripts/run_dual_axis_review.py

# If reviewing another project (global install):
REVIEWER=~/.claude/skills/dual-axis-skill-reviewer/scripts/run_dual_axis_review.py

Step 1: Run Auto Axis + Generate LLM Prompt

uv run "$REVIEWER" \
  --project-root . \
  --emit-llm-prompt \
  --output-dir reports/

--project-root

uv run "$REVIEWER" \
  --project-root /path/to/other/project \
  --emit-llm-prompt \
  --output-dir reports/

Step 2: Run LLM Review

• Use the generated prompt file in

  reports/skill_review_prompt_<skill>_<timestamp>.md

  .
• Ask the LLM to return strict JSON output.
• When running inside Claude Code, let Claude act as orchestrator: read the generated prompt, produce the LLM review JSON, and save it for the merge step.

Step 3: Merge Auto + LLM Axes

uv run "$REVIEWER" \
  --project-root . \
  --skill <skill-name> \
  --llm-review-json <path-to-llm-review.json> \
  --auto-weight 0.5 \
  --llm-weight 0.5 \
  --output-dir reports/

Step 4: Optional Controls

• Fix selection for reproducibility:

  --skill <name>

  or

  --seed <int>

• Review all skills at once:

  --all

• Skip tests for quick triage:

  --skip-tests

• Change report location:

  --output-dir <dir>

• Increase

  --auto-weight

  for stricter deterministic gating.
• Increase

  --llm-weight

  when qualitative/code-review depth is prioritized.

Output

• reports/skill_review_<skill>_<timestamp>.json

• reports/skill_review_<skill>_<timestamp>.md

• reports/skill_review_prompt_<skill>_<timestamp>.md

  (when

  --emit-llm-prompt

  is enabled)

Installation (Global)

~/.claude/skills/

ln -sfn /path/to/claude-trading-skills/skills/dual-axis-skill-reviewer \
  ~/.claude/skills/dual-axis-skill-reviewer

~/.claude/skills/dual-axis-skill-reviewer/scripts/run_dual_axis_review.py

Resources

• Auto axis scores metadata, workflow coverage, execution safety, artifact presence, and test health.
• Auto axis detects

  knowledge_only

  skills and adjusts script/test expectations to avoid unfair penalties.
• LLM axis scores deep content quality (correctness, risk, missing logic, maintainability).
• Final score is weighted average.
• If final score is below 90, improvement items are required and listed in the markdown report.
• Script:

  skills/dual-axis-skill-reviewer/scripts/run_dual_axis_review.py

• LLM schema:

  skills/dual-axis-skill-reviewer/references/llm_review_schema.md

• Rubric detail:

  skills/dual-axis-skill-reviewer/references/scoring_rubric.md