AC voice-excel-editor
Use when: 用户要上传 Excel 文件和一段语音指令，希望把语音中的表格编辑要求转成结构化 Excel 操作并落到工作簿里时触发。 适用于格式调整、数据写入、基础计算、行列结构修改、多步顺序编辑，以及需要输出执行日志和修改后 Excel 文件的场景。Skill 会先做语音转写与文本规范化，再让 Agent 生成操作计划，最后由脚本执行 Excel 改写并返回结果摘要。
Use when: 用户要上传 Excel 文件和一段语音指令，希望把语音中的表格编辑要求转成结构化 Excel 操作并落到工作簿里时触发。 适用于格式调整、数据写入、基础计算、行列结构修改、多步顺序编辑，以及需要输出执行日志和修改后 Excel 文件的场景。Skill 会先做语音转写与文本规范化，再让 Agent…
As a process C 51/100 · Has gaps — 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
- 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
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medium Exfiltration
net-redirectable-api-keyscripts/main.py:143Helper 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: 7. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 51/100
- 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. 3 mutating operations with no state check
- 100Tools and files. No external tools needed
- 100Steps. 108 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1217 tokens
- 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 190: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 108 items
- +4Has examples (10 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.