BD tech-transfer-target-discovery
央企科技成果对外输出——对接对象发现工具。用户输入拟输出的专利号或技术描述，先调用智慧芽MCP提取资产技术特征，再识别输出路径（许可/转让/作价入股/质押佐证），执行三轨检索并输出有专利证据支撑的目标企业短名单及推荐对接路径。
央企科技成果对外输出——对接对象发现工具。用户输入拟输出的专利号或技术描述，先调用智慧芽MCP提取资产技术特征，再识别输出路径（许可/转让/作价入股/质押佐证），执行三轨检索并输出有专利证据支撑的目标企业短名单及推荐对接路径。
As a process D 44/100 · 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: 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") - note
frontmatter-keyunknown frontmatter key "copyright"
Process rating: all ten parameters 44/100
- 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
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 70Execution cost. Instruction body is 4010 tokens
- 100Steps. 168 steps
- 100Consistency. Name and required fields are in place
- 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
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 113: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 18 headings
- +3Step-by-step instructions: 168 items
- +4Has examples (5 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.
External checks
ClawHub: clean
This skill is a disclosed patent-transfer research workflow that uses Patsnap MCP and web search to generate evidence-based target-company reports.
LLM: benign (high) · VirusTotal: · 13 Aug 2026