CD office-collaboration-radar
从群聊记录、会议纪要等协作材料中提取稳定格式的协作状态卡片。 用户提到"协作状态""项目进展""待办提取""风险阻断""Owner/DDL""跨部门依赖""需确认项" 或粘贴协作文本时使用；输出协作状态卡片、行动项、风险依赖、证据片段、优先级排序、 雷达图与 JSON 结构化结果，并自动脱敏常见 PII 与凭据、重新核验全部证据、标记冲突； 只读取用户明确指定的本地文件，落盘时必须提供明确的输出路径。
从群聊记录、会议纪要等协作材料中提取稳定格式的协作状态卡片。 用户提到"协作状态""项目进展""待办提取""风险阻断""Owner/DDL""跨部门依赖""需确认项" 或粘贴协作文本时使用；输出协作状态卡片、行动项、风险依赖、证据片段、优先级排序、 雷达图与 JSON 结构化结果，并自动脱敏常见 PII…
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 · 2
✓ No critical or high findings
Medium and low: 2
-
low Secrets in code
secret-labelled-tokenscripts/process.py:686Labelled token / key literal (vendor format unknown — verify it is not a live credential) (placeholder value)"api_key=sk-1…jkl Authorization: Bearer abcdefghijklmnop "
placeholder -
low Secrets in code
secret-password-literalscripts/process.py:686Hard-coded password / key literal (may be an example) (placeholder value)"api_key=sk-1…jkl Authorization: Bearer abcdefghijklmnop "
placeholder
Files scanned: 26. 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 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, python) that frontmatter does not declare
- 100Steps. 80 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1945 tokens
- 100Running it twice. No mutating operations
- low 11 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
- +1No license
- +2Single-language instructions
- +3Description length 202: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 80 items
- +4Has examples (4 code blocks)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.