AD autopilot
自动循环编排引擎 — Plan(OMC opus) → Build(OMX) → Verify(Orchestrator) 循环执行复杂任务，最多5轮自动收敛。当用户提到"自动执行"、"循环执行"、"帮我自动完成"、需要多步验证的复杂重构、自动修复循环、多模块联动修改时触发。即使用户没有明确说"autopilot"，只要任务复杂度需要计划→执行→验证→修复的循环，就应该建议使用本技能。简单单文件修改直接派发 OMC 或 OMX 即可。
As a process D 41/100 · 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.
For the model run — optional
- 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: 4. 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 "source" - note
frontmatter-keyunknown frontmatter key "created_at" - note
frontmatter-keyunknown frontmatter key "updated_at"
Process rating: all ten parameters 41/100
- 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
- 40Consistency. Frontmatter name (autopilot) differs from the folder (autopilot-pbv)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 69 steps
- 100Execution cost. Instruction body is 2057 tokens
- 100Running it twice. No mutating operations
- low 13 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (3 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
- +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
- +5Description quotes 2 example trigger phrases
- +3Description length 219: enough signal without eating the budget
- +4Structure: 22 headings
- +3Step-by-step instructions: 69 items
- +4Has examples (7 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.
External checks
ClawHub: suspicious
This is a coherent autonomous coding skill, but it defaults to broad file-changing execution with sandbox and permission bypasses, so it should be reviewed carefully before use.
LLM: suspicious (high) · VirusTotal: · 29 May 2026