Content
100%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A well-structured integration skill body: actionable commands, explicit processing chains with retry/validation guardrails, and clean one-level progressive disclosure into verified reference files. It assumes Claude's competence and avoids concept explanations.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense operational guidance — routing rules, a command table, processing chains, an error-code decision tree — with no padding or explanation of concepts Claude already knows; minor inter-section restatement is operationally load-bearing rather than filler. | 3 / 3 |
Actionability | Concrete executable commands throughout: a per-task command table mapping to reference files, explicit topic codes ('topic：1待办 2已办 17未读 18已读'), copy-paste bash examples, and a parameter-pairing rule ('instance_code + task_id 必须成对带上'). | 3 / 3 |
Workflow Clarity | Multi-step chains are explicit ('approvals search -> approvals get -> instances create'; 'tasks query ... → instances get → 执行操作') with validation checkpoints and a feedback loop: the 1395001 decision tree caps retries at 1 and forbids the query/write loop. | 3 / 3 |
Progressive Disclosure | The SKILL.md is an overview that points to one-level-deep reference files via a clearly signaled table, each reference (e.g. lark-approval-tasks-approve.md, lark-approval-initiate.md) verified to exist in ./references/, with 'references 是第一信息源' establishing navigation priority. | 3 / 3 |
Total | 12 / 12 Passed |