BD acceptance-rate-analysis
对承接率下降做阶段式归因分析。适用于“今天/本周承接率为什么下降”“分析承接率下降原因”“看一下承接率环比是否下降及原因”等场景。先定位异常切片，再逐层判断是一级切片结构迁移、资方总量明显减少或分布左移、资产维度异常，还是进一步闭环到敏感资方侧收缩。
As a process D 40/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
This is a copy of a skill from another catalog; the rating counts the canonical one: acceptance-rate-analysis (ClawHub)
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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: 7. 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
body-longSKILL.md body ≈ 5636 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 40/100
- 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
- 40Consistency. Frontmatter name (acceptance-rate-analysis) differs from the folder (acceptance-rate-analysis-new)
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 70Execution cost. Instruction body is 5636 tokens
- 100Steps. 208 steps
- 100Running it twice. No mutating operations
- low 12 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (8 tags): a typed call is more reliable
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
- -214 emoji in the instructions: noise for the model
- -31 of 4 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +5Description quotes 3 example trigger phrases
- +3Description length 125: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 208 items
- +4Has examples (11 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.
External checks
ClawHub: suspicious
This skill appears intended for internal acceptance-rate analytics, but it automatically persists a sensitive browser-derived access token and can send it to configurable endpoints.
LLM: suspicious (high) · VirusTotal: · 9 Jun 2026