BC patent-portfolio-report
麦肯锡标准·专利组合解读分析报告交付Skill。输入分析标的（企业名称/专利清单/技术领域/竞争对手）及客户核心诉求，严格遵循10步SOP，按九大模块输出完整中文HTML专利组合分析报告，内含核心专利技术拆解可视化图、麦肯锡深蓝配色体系、金字塔原则排版。所有专利数据强制通过Patsnap实时检索，每模块末尾列明检索式备注。集成novelty-check、non-obviousness-check、triz-analysis、patsnap-mckinsey-sales-insight、patsnap-visit-strategist子技能流水线。适用场景：IPO尽调、并购估值、研发战略、337诉讼应对、企业出海布局、行业竞争格局分析。触发关键词：专利组合分析、专利尽调报告、专利价值评估、专利竞争格局、核心专利拆解、IPO知识产权尽调、专利战略报告、专利组合解读、麦肯锡专利报告。
麦肯锡标准·专利组合解读分析报告交付Skill。输入分析标的（企业名称/专利清单/技术领域/竞争对手）及客户核心诉求，严格遵循10步SOP，按九大模块输出完整中文HTML专利组合分析报告，内含核心专利技术拆解可视化图、麦肯锡深蓝配色体系、金字塔原则排版。所有专利数据强制通过Patsnap实时检索，每模块末尾列明检索式…
As a process C 52/100 · 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") - note
frontmatter-keyunknown frontmatter key "copyright"
Process rating: all ten parameters 52/100
- 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
- 70Execution cost. Instruction body is 4947 tokens
- 100Tools and files. No external tools needed
- 100Steps. 88 steps
- 100Consistency. Name and required fields are in place
- 100Running it twice. No mutating operations
- low 17 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
- +1No license
- +2Single-language instructions
- +3Description length 394: enough signal without eating the budget
- +4Structure: 47 headings
- +3Step-by-step instructions: 88 items
- +4Has examples (6 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.