Content
67%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A well-organized skill with genuinely executable tooling, clear six-step workflows, and explicit validation checklists. The main costs are token redundancy (command blocks repeated three times, generic PM advice inlined), one documented CLI invocation that does not match the script's actual flags, and an orphaned assets/ directory.
Suggestions
Fix the customer_interview_analyzer examples to use the script's actual flag ("python scripts/customer_interview_analyzer.py interview.txt --json") — the documented positional 'json' argument fails as written in all three places it appears.
De-duplicate the command blocks: keep one canonical set (e.g., in Tools Reference) and trim the Quick Start / Quick Reference repeats, and move the Best Practices and Integration Points sections into references/frameworks.md to cut generic PM knowledge from the main file.
Reference the assets/ files (prd_template.md, rice_input_template.csv) from the relevant workflow sections, or remove them from the bundle so every file is discoverable from SKILL.md.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly terse bullets, tables, and checklists, but the same rice_prioritizer commands appear nearly verbatim three times ("Quick Start", "Tools Reference"/"Integration Points", and "Quick Reference"), and the "Integration Points" platform table and "Best Practices" sections restate product-management knowledge Claude already has. This matches "mostly efficient but includes some unnecessary explanation or could be tightened" rather than 4, where over-explanation would be only minor. | 3 / 5 |
Actionability | Most guidance is concrete and executable — real commands ("python scripts/rice_prioritizer.py features.csv --capacity 20"), a CSV input format spec, a template selection table, and a sample-data subcommand verified against the actual scripts. It is not 5 because the documented "python scripts/customer_interview_analyzer.py interview.txt json" command is wrong (the script takes a --json flag, not a positional argument, so the command as written fails), and it is not 3 because the remaining commands are copy-paste ready. | 4 / 5 |
Workflow Clarity | All three processes ("Gather → Score → Analyze → Plan → Validate → Execute", etc.) have six clearly sequenced steps with explicit validation checklists ("Before finalizing the roadmap: [ ] Run sensitivity analysis..."). It falls short of 5 because the checklists say what to verify but give no error-recovery guidance for a failed check (no validate → fix → retry loop), which the 5 anchor requires. | 4 / 5 |
Progressive Disclosure | Good structure: reference files are real, one level deep, and clearly signaled both inline ("See `references/frameworks.md` for RICE formula") and in a closing "Reference Documents" section. It is not 5 because the `assets/` bundle files (prd_template.md, rice_input_template.csv) are never referenced from SKILL.md, and the "Input/Output Examples" section is just a bare arrow pointer ("→ See references/input-output-examples.md for details") while generic Best Practices/Integration Points content that could live in a reference is inlined. | 4 / 5 |
Total | 15 / 20 Passed |