Content
77%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-structured, highly actionable skill that clearly orchestrates a complex multi-agent workflow with proper validation checkpoints and error handling. Its main weaknesses are moderate verbosity from repeated content (the AI instruction file list appears 4 times) and being a monolithic document that could benefit from splitting agent prompt templates into separate files. The workflow design with user checkpoint gating and parallel agent dispatch is excellent.
Suggestions
Extract the repeated list of AI assistant instruction files into a single variable or reference at the top, then refer to it throughout instead of repeating the full list 4 times.
Consider splitting the three agent prompt templates into a separate reference file (e.g., AGENT-PROMPTS.md) to reduce the main skill's length and improve progressive disclosure.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is quite long (~300 lines) and contains some repetition (e.g., the full list of AI assistant instruction files is repeated 4 times verbatim). However, most content is genuinely instructional and not explaining concepts Claude already knows. The agent prompt templates are necessarily verbose but could be more concise. | 2 / 3 |
Actionability | The skill provides highly concrete, executable guidance: specific git commands, exact file paths to check, precise agent prompt templates, structured output formats, and clear decision trees. Every step tells Claude exactly what to do, with specific commands and file globs. | 3 / 3 |
Workflow Clarity | The 5-phase workflow is clearly sequenced with explicit checkpoints: Phase 1 discovery → Phase 2 parallel agents → Phase 3 user checkpoint (explicit gate before proceeding) → Phase 4 fix agent → Phase 5 summary. The user checkpoint in Phase 3 is a strong validation gate. Error handling table covers edge cases. The retry logic for failed agents provides a feedback loop. | 3 / 3 |
Progressive Disclosure | The skill is a monolithic document with no references to supporting files. While the content is well-structured with clear headers and phases, the agent prompt templates and detailed discovery instructions could be split into separate reference files. The review-config.md and ARCHITECTURE.md references are good external integration points, but the skill itself is a long single file with no bundle support. | 2 / 3 |
Total | 10 / 12 Passed |