AC retail-target-tracking-analysis
门店目标追踪分析工具。支持日/周/月三周期目标追踪，T-N数据延迟，黄绿黄灯状态预警。 核心能力： 1. 三周期追踪（日追踪-晨会/实时预警、周追踪-周会复盘、月追踪-月度考核） 2. T-N数据延迟支持（默认T-1） 3. 黄绿黄灯状态（🟢正常、🟡关注、🟠警告、🔴告警/紧急） 4. 批量告警检查（检查所有门店，按优先级排序） 5. 定时任务预留接口 触发条件： - 用户询问目标达成（如"本月目标达成率"） - 用户需要预警（如"哪些门店需要关注"） - 用户追踪业绩（如"业绩进度如何"）
As a process C 53/100 · Has gaps — 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.
For the model run — optional
- 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: 5. 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 53/100
- 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
- 100Tools and files. No external tools needed
- 100Steps. 5 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 349 tokens
- 100Running it twice. No mutating operations
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
- +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
- +5Description quotes 3 example trigger phrases
- +3Description length 253: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 5 items
- +4Has examples (4 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.
External checks
ClawHub: suspicious
This skill appears useful for store BI analysis, but it can access broader business data than its stated store-level scope clearly discloses.
LLM: suspicious (medium) · VirusTotal: · 29 May 2026