Content
87%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is concise, highly actionable, and well-structured with appropriate one-level external references. Its main gap is the absence of an explicit validation/feedback loop for verifying a generated Skill or guarding destructive writes.
Suggestions
Add an explicit verification step for produced Skills (e.g. run a dry-run or smoke-test command against a sandbox tenant before delivery) with a fix→retry loop.
Expand the destructive-write guidance from a one-line suggestion into a concrete validate-then-confirm checkpoint in the workflow.
Note that no references/ or scripts/ bundle exists; if detailed scope tables or templates grow, move them into reference files to preserve the lean overview.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean and efficient throughout — concrete CLI commands, a compact template, and terse principle bullets with no padding or re-explanation of concepts Claude already knows. | 3 / 3 |
Actionability | Provides fully executable lark-cli commands with real flags (--params, --data), real API paths, and a copy-paste-ready SKILL.md template with concrete examples. | 3 / 3 |
Workflow Clarity | Sequences the research flow (numbered 1-3) with a fallback escalation and template Step 1/Step 2 data passing, but lacks an explicit validate→fix→retry checkpoint for the produced Skill or destructive writes, which the rubric caps at 2. | 2 / 3 |
Progressive Disclosure | Well-organized into clear sections with one-level-deep, clearly signaled external references (../lark-openapi-explorer, ../lark-shared) and no nested references; appropriate for a compact skill with no bundle directory. | 3 / 3 |
Total | 11 / 12 Passed |