AD cogniexec
认知执行技能 — 整合认知套件与执行框架两大能力层，并配备编排引擎。 认知层：四种思维操作码（直用/改进/迁移/构建）覆盖所有思考任务； 执行层：大语言模型 + 命令执行工具，自动化代码生成与脚本执行； 编排引擎：将所有操作统一为基元，自由组合为任意复杂度的执行链条。 此技能应用于认知与代码执行类任务。
As a process D 48/100 · 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: 21. 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 48/100
- 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
- 20When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 15 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1982 tokens
- 100Running it twice. No mutating operations
- 100Progress reporting. Reports progress
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
- -5TODO / placeholder text left in the skill
- +1No license
- +2Single-language instructions
- +3Description length 152: enough signal without eating the budget
- +4Structure: 23 headings
- +3Step-by-step instructions: 15 items
- +4Has examples (7 code blocks)
- +4Reference files are cited in the instructions (1 of 2)
- +3All 17 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.
External checks
ClawHub: suspicious
This skill is a broad automation toolkit with disclosed but high-impact command, file, network, email, clipboard, and data-processing powers that are not scoped tightly enough for default trust.
LLM: suspicious (high) · VirusTotal: · 29 May 2026