BD industry-research
行业研究分析框架与报告撰写技能。覆盖触发场景：(1) 用户要求分析某行业/赛道/市场，撰写行业研究报告、深度分析、快评、对标分析， (2) 研究公司竞争格局、商业模式、产业链，(3) 进行跨国/跨市场对比，(4) 评估行业风险与趋势， (5) 需要专家访谈提纲设计或信息来源评级。方法论核心：五维度分析框架 + 三步研究法 + 假设驱动 + 定量锚点 + 全球对标。
As a process D 49/100 · 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.
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 49/100
- 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 (industry-research) differs from the folder (industry-research-framework)
- 100Tools and files. No external tools needed
- 100Steps. 30 steps
- 100Execution cost. Instruction body is 630 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
- +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
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 183: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 30 items
- +4Reference files are cited in the instructions (3 of 3)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.
External checks
ClawHub: clean
This is a text-only industry research and report-writing framework with no code, install hooks, credential access, persistence, or hidden behavior found.
LLM: benign (high) · VirusTotal: · 29 May 2026