AC ipo-model
输入处理输出结构递归嵌套模型 — 万物基元与世界模型。 一切任务均可分解为 输入→处理→输出 的递归嵌套结构，任意层级的任意节点均可继续展开为子IPO。 不使用工具时：用IPO分析问题、生成产物（纯认知输出）。 使用工具时：在IPO分析产物基础上，进一步用IPO生成命令、脚本，调用 Tool / Skill / MCP。 工具调用层级：command → script → Tool → Skill → MCP，由简到繁逐级升级。 此技能是认知世界和改造世界的统一方法论，适用于所有类型的任务。
As a process C 53/100 · Has gaps — 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: 3. 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")
Process rating: all ten parameters 53/100
- 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
- 100Tools and files. No external tools needed
- 100Steps. 6 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1548 tokens
- 100Running it twice. No mutating operations
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
- +1No license
- +2Single-language instructions
- +3Description length 248: enough signal without eating the budget
- +4Structure: 23 headings
- +3Step-by-step instructions: 6 items
- +4Has examples (14 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.
External checks
ClawHub: suspicious
The skill does not show malicious behavior, but its very broad scope and under-specified examples could lead an agent to modify files or handle private data without enough safeguards.
LLM: suspicious (medium) · VirusTotal: · 29 May 2026