CF office-token-booster
办公室 AI 提效助手 —— 既帮你做周报/会议纪要/数据分析/文档整理/PPT 大纲，又自动记下每次帮你省了多少 Token 和时间。执行与度量一体：做完任务顺手记一笔，省了多少一目了然。适用于办公生产力执行、AI 用量洞察、提效度量与自动化决策场景。
办公室 AI 提效助手 —— 既帮你做周报/会议纪要/数据分析/文档整理/PPT 大纲，又自动记下每次帮你省了多少 Token 和时间。执行与度量一体：做完任务顺手记一笔，省了多少一目了然。适用于办公生产力执行、AI 用量洞察、提效度量与自动化决策场景。
As a process F 33/100 · No process to follow — References files that are not bundled: scripts/clawhub_client.py, scripts/skillhub_client.py, scripts/security_preflight.py
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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: 24. 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
missing-refreference to a missing file: scripts/clawhub_client.py - warning
missing-refreference to a missing file: scripts/skillhub_client.py - warning
missing-refreference to a missing file: scripts/security_preflight.py - note
frontmatter-keyunknown frontmatter key "categories" - note
frontmatter-keyunknown frontmatter key "triggers" - note
frontmatter-keyunknown frontmatter key "non_triggers" - note
frontmatter-keyunknown frontmatter key "tools" - note
frontmatter-keyunknown frontmatter key "network"
Process rating: all ten parameters 33/100
- 0Tools and files. 3 referenced file(s) missing: scripts/clawhub_client.py, scripts/skillhub_client.py, scripts/security_preflight.py
- 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. 2 mutating operations with no state check
- 100Steps. 54 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3057 tokens
- low 15 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
- -41 reference files, but SKILL.md never points to them: the model will not open them
- -34 of 12 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 127: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 54 items
- +4Has examples (9 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 50.