Content
85%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-structured, actionable skill body with clear workflow sequencing and good progressive disclosure through real reference files. Conciseness and actionability are strong but have minor room for tightening and making the dispatch examples fully executable.
Suggestions
Trim rationale restatements like '**Why research first?**' and 'prevents thrashing and discovers constraints early' since the Purpose section already conveys the motivation.
Show the Task dispatch calls in their full executable form (with subagent_type and run_in_background parameters) rather than the abbreviated `Task(Explore): "..."` signatures.
Collapse the redundant depth-signals table or fold the 'Quick' rows into prose to reduce token weight on the less-common depth choices.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Largely efficient with tight tables and a focused workflow, but a few sections restate the rationale (e.g. '**Why research first?**', 'prevents thrashing and discovers constraints early') that could be trimmed. | 4 / 5 |
Actionability | Provides concrete dispatch examples, named subagent types, exact output paths, and a referenced template — but the Task tool calls are shown as pseudocode signatures rather than fully executable calls. | 4 / 5 |
Workflow Clarity | A clear 6-step sequence with explicit checkpoints — a REQUIRED user-review step, 'do NOT dispatch a follow-up agent' guardrail, and anti-patterns — giving robust feedback loops; no destructive/batch operation cap applies. | 5 / 5 |
Progressive Disclosure | Well-organized overview with clearly signaled, one-level-deep references to real bundle files (references/agent-prompts.md, references/template.md), keeping the body lean while offloading detail. | 5 / 5 |
Total | 18 / 20 Passed |