CD work2cli-hitl
指导把日常工作沉淀成 CLI 工具集 + agent skill 的工作台，并对写操作接入飞书审批形成极简 HITL（Human-In-The-Loop）。用户只需给一个网站/系统地址，agent 自主勘察 API 面貌、识别哪些功能是写、自行炼化成 CLI。触发条件：用户想把日常/重复工作做成命令行工具、丢来一个平台网址说「帮我把这个做成工具」、想给 CLI 的写操作加审批/二次确认、提到 write-guard/写守卫/HITL/Human-In-The-Loop/飞书审批/守卫守护进程/全局守卫、想搭「CLI + skill」工作台、做完 CLI 要求沉淀使用说明/更新注册表/自进化。
指导把日常工作沉淀成 CLI 工具集 + agent skill 的工作台，并对写操作接入飞书审批形成极简 HITL（Human-In-The-Loop）。用户只需给一个网站/系统地址，agent 自主勘察 API 面貌、识别哪些功能是写、自行炼化成…
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 12. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "summary"
Process rating: all ten parameters 46/100
- 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
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 100Steps. 44 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1592 tokens
- 100Running it twice. No mutating operations
- low 12 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (4 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
- +2Single-language instructions
- +3Description length 299: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 44 items
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.