AD wechat-similar-account
公众号创作者对标账号匹配工具，基于3层加权匹配体系（核心基础40%+运营变现35%+数据特征25%）推荐对标账号和头部账号。当用户需要公众号账号推荐、公众号对标、起号参考、账号投放选择时使用。触发词：公众号对标、相似账号、对标推荐、起号参考、账号匹配。
公众号创作者对标账号匹配工具，基于3层加权匹配体系（核心基础40%+运营变现35%+数据特征25%）推荐对标账号和头部账号。当用户需要公众号账号推荐、公众号对标、起号参考、账号投放选择时使用。触发词：公众号对标、相似账号、对标推荐、起号参考、账号匹配。
As a process D 43/100 · 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 Dangerous commands
cmd-shell-rcSKILL.md:52Writes to a shell startup file (documentation table row)| macOS/Linux | `echo 'export REDFOX_API_KEY=<值>' >> ~/.zshrc && source ~/.zshrc` | `echo $REDFOX_API_KEY` |
table -
low Dangerous commands
cmd-shell-rcSKILL.md:261Writes to a shell startup file (quoted — discussed, not commanded)3. macOS/Linux 用户执行：`echo 'export REDFOX_API_KEY=<你的API Key>' >> ~/.zshrc` 然后 `source ~/.zshrc`
quoted
Files scanned: 6. 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 43/100
- 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. 2 mutating operations with no state check
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 100Steps. 58 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1823 tokens
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
- -215 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 126: enough signal without eating the budget
- +4Structure: 37 headings
- +3Step-by-step instructions: 58 items
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.