AD industry-research
产学研合作调研。当用户要求对某家企业（如百度、阿里、华为、科大讯飞等）做合作调研、产业调研、合作可行性分析、研究方向匹配、对接准备时触发。输出包括：企业画像、研究方向交叉匹配、合作切入点、参会人员建议，以及可选的会议议程。也适用于用户说"帮我看看XX公司能不能合作""调研一下XX"等场景。
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 (zhongguancun-industry-research)
- 100Tools and files. No external tools needed
- 100Steps. 19 steps
- 100Execution cost. Instruction body is 268 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
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 2 example trigger phrases
- +3Description length 145: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 19 items
- +4Reference files are cited in the instructions (2 of 3)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.
External checks
ClawHub: clean
This is a low-risk Chinese-language research skill for public company partnership analysis, with no executable code or hidden access.
LLM: benign (high) · VirusTotal: · 29 May 2026