| name | dual-axis-skill-reviewer |
| description | Review skills in any project using a dual-axis method: (1) deterministic code-based checks (structure, scripts, tests, execution safety) and (2) LLM deep review findings. Use when you need reproducible quality scoring for `skills/*/SKILL.md`, want to gate merges with a score threshold (for example 90+), or need concrete improvement items for low-scoring skills. Works across projects via --project-root. |
Dual Axis Skill Reviewer
Run the dual-axis reviewer script and save reports to reports/.
The script supports:
- 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
Determine the correct script path based on your context:
- 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
The examples below use REVIEWER as a placeholder. Set it once:
REVIEWER=skills/dual-axis-skill-reviewer/scripts/run_dual_axis_review.py
REVIEWER=~/.claude/skills/dual-axis-skill-reviewer/scripts/run_dual_axis_review.py
Step 1: Run Auto Axis + Generate LLM Prompt
uv run "$REVIEWER" \
--project-root . \
--emit-llm-prompt \
--output-dir reports/
When reviewing a different project, point --project-root to it:
uv run "$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>.jsonreports/skill_review_<skill>_<timestamp>.mdreports/skill_review_prompt_<skill>_<timestamp>.md (when --emit-llm-prompt is enabled)
Installation (Global)
To use this skill from any project, symlink it into ~/.claude/skills/:
ln -sfn /path/to/claude-trading-skills/skills/dual-axis-skill-reviewer \
~/.claude/skills/dual-axis-skill-reviewer
After this, Claude Code will discover the skill in all projects, and the script is accessible at ~/.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:
references/llm_review_schema.md
- Rubric detail:
references/scoring_rubric.md
