Content
77%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The content is highly actionable with a clearly sequenced, validated workflow and robust error handling for batch operations, but it is a long monolithic file with some repetition that slightly hurts token efficiency and would benefit from splitting detail into a reference file.
Suggestions
Move the agent-check JSON field reference and ASCII status-table formats into a referenced file (e.g. references/agent-check-schema.md) and summarize in SKILL.md to improve progressive disclosure.
Trim the "Important Notes" section by removing rules already stated inline in Steps 2–3 to reduce repetition and token cost.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly efficient command snippets and decision tables without explaining basic concepts, but it runs ~360 lines with some repetition — e.g. "Important Notes" restates rules already given in Steps 2–3, and the ASCII status tables add length that could be trimmed. | 2 / 3 |
Actionability | It provides copy-paste-ready, fully executable commands (yarn agent:check, gh api REST/GraphQL calls, gh run view) and a concrete decision matrix mapping CI/thread states to actions. | 3 / 3 |
Workflow Clarity | Steps 0–4 are clearly sequenced with explicit validation checkpoints (per-iteration PR state check, CI bucket classification) and feedback loops (fix → push → wait → re-check), plus non-blocking error handling for the batch thread-resolution work. | 3 / 3 |
Progressive Disclosure | The skill is a single well-organized SKILL.md with no bundle files, but at ~360 lines it is monolithic; reference material like the agent-check JSON schema and status-table formats could be split into a referenced file rather than inlined. | 2 / 3 |
Total | 10 / 12 Passed |