AC analysis-report
编排并生成完整的数据分析报告。当用户需要一份结构化的分析报告（而非单个指标查询或单点分析）时，必须使用此 Skill。本 Skill 是编排层——它不包含分析逻辑，而是知道"一份好报告该有什么内容"，按报告模板依次调度能力层 Skill（metric-query、anomaly-detection、metric-attribution、forecast-simulation）执行各板块分析，最后将结果串联为连贯的分析叙事。 触发场景包括但不限于：用户提到"出一份报告""月报""周报""分析报告""汇报""工作总结""经营分析""数据复盘""业绩回顾""出一份XX分析""帮我做个报告""总结一下上月情况""给老板看的报告""经营简报""数据报告"，或用户希望对某个业务领域做一次全面、系统的分析并输出文档时，都应使用此 Skill。 **触发判定关键**：用户想要的是一份**完整的、多板块的分析文档**，而非单个数据点查询或单项分析。区分方式： - "出一份月报""做个销售分析报告" → analysis-report（完整报告） - "上月销售额多少" → metric-query（单个数据查询） - "销售额有没有异常" → anomaly-detection（单项异常检测） - "以后每月都出月报" → scheduled-report（含"以后/每月"=定时意图） **与 scheduled-report 的区分**：本 Skill 管"现在就出一份报告"（一次性执行）；scheduled-report 管"以后定期出"（录制+定时重放）。判断依据是用户表达中是否包含"定时/定期/每X/以后都"等重复执行意图。没有 → 本 Skill；有 → scheduled-report。 **前提**：本 Skill 不直接查数据或做分析，所有分析工作委派给能力层 Skill。它的核心价值是报告结构知识和叙事编排能力。
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.
- 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: 2. 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. 16 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1697 tokens
- 100Running it twice. No mutating operations
- low 10 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 820: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 11 example trigger phrases
- +4Structure: 24 headings
- +3Step-by-step instructions: 16 items
- +4Has examples (5 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.