AD openapi-lark
把项目 OpenAPI / Swagger spec（本地 yaml/json **或 http(s):// URL**）同步到飞书 / Lark wiki & docx 文档树。支持 single / tree / endpoint（每接口一个 wiki 子节点）三种结构，自动按 tag 拆分 + path-prefix 分子组，中文优先标题、allOf 扁平化、响应字段表 + JSON 示例、hash 缓存、dry-run 真不推线上。对接 chanfana / Hono / FastAPI / NestJS Swagger 的 runtime /openapi.json 端点。用于替代 yapi 文档管线。Trigger 当用户说「同步接口文档到飞书」「openapi 推到飞书」「openapi 推到 lark」「替换 yapi」「lark docs from openapi」「swagger to feishu」「飞书 API 文档自动化」「按 tag 拆文档」「每个接口一个文档」「runtime openapi URL 同步」「chanfana / Hono / FastAPI openapi 推到飞书」「openapi-lark」时。
把项目 OpenAPI / Swagger spec（本地 yaml/json 或 http(s):// URL）同步到飞书 / Lark wiki & docx 文档树。支持 single / tree / endpoint（每接口一个 wiki 子节点）三种结构，自动按 tag 拆分 + path-prefix…
As a process D 42/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 42/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 23 mutating operations with no state check
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 70Execution cost. Instruction body is 4532 tokens
- 100Steps. 75 steps
- 100Consistency. Name and required fields are in place
- low 17 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (14 tags): a typed call is more reliable
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -212 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 531: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 75 items
- +4Has examples (12 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.