Content
77%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A well-structured, actionable, and well-validated workflow with concrete executable commands. The main weaknesses are an inline reference taxonomy that could be externalized and trimmed, affecting both conciseness and progressive disclosure.
Suggestions
Move the full Graph Structure Reference (node/edge type taxonomy) into a separate file such as references/graph-structure.md and keep only the essential summary inline, improving both conciseness and progressive disclosure.
Trim the exhaustive edge-type and node-type lists to only the types the onboarding workflow uses (file-level types, layers, tour), cutting tokens that do not earn their place for this specific task.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and avoids generic-concept padding, but the exhaustive node-type and edge-type taxonomy in 'Graph Structure Reference' is more reference material than the onboarding workflow actually consumes. | 2 / 3 |
Actionability | Steps include fully executable, copy-paste-ready bash (the UA_DIR resolution and git diff block) and specific Grep targets like '"layers"' and '"tour"'. | 3 / 3 |
Workflow Clarity | Eleven sequenced steps with an explicit validation checkpoint (graph-freshness check in step 2) and a feedback loop ('Run /understand to refresh the graph') for error recovery. | 3 / 3 |
Progressive Disclosure | Sections are well-organized and there are no bundle files, but the sizable Graph Structure Reference block is reference-style content kept inline in a skill over 50 lines rather than split into a separate file. | 2 / 3 |
Total | 10 / 12 Passed |