BD comind
CoMind 人机协作平台 AI 成员操作手册。定义任务执行、Markdown 同步、对话协作、状态面板等全部工作流程。当 AI 成员接收到 CoMind 平台的任务推送、对话请求、定时调度或巡检指令时，应使用此 Skill 执行标准化操作。
CoMind 人机协作平台 AI 成员操作手册。定义任务执行、Markdown 同步、对话协作、状态面板等全部工作流程。当 AI 成员接收到 CoMind 平台的任务推送、对话请求、定时调度或巡检指令时，应使用此 Skill 执行标准化操作。
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".
If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
medium Exfiltration
net-redirectable-api-keyscripts/render-template.py:158Helper sends the API key to a host configured by an environment variable — the key can be redirected to another serverAPI key + configurable base URL from environment
Files scanned: 14. 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") - warning
body-longSKILL.md body ≈ 6920 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "comind_version"
Process rating: all ten parameters 49/100
- 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. 18 mutating operations with no state check
- 70Execution cost. Instruction body is 6920 tokens
- 100Tools and files. No external tools needed
- 100Steps. 95 steps
- 100Consistency. Name and required fields are in place
- low 17 top-level sections: this looks like several domains in one skill
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
- -2localhost URLs: will not work for another user
- -275 emoji in the instructions: noise for the model
- -31 of 1 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 121: enough signal without eating the budget
- +4Structure: 61 headings
- +3Step-by-step instructions: 95 items
- +4Has examples (54 code blocks)
- +4Reference files are cited in the instructions (4 of 12)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 53.