AC patent-panorama-insights
当用户需要基于 PatSnap 或智慧芽专利 MCP/API 数据开展专利全景、专利版图、竞争专利情报、技术路线图、组合规划、产品/R&D 策略项目时使用本技能——无论用户显式调用 /patent-panorama-insights（或 @patent-panorama-insights），还是用自然语言描述这类专利分析任务。本技能编排五层流水线：环节1检索与降噪（patent-panorama-insights-search）、环节2全景统计与价值挖掘（patent-panorama-insights-stats）、环节3标引体系推荐（patent-panorama-insights-tag）、客户 SaaS 工具中的人工标引交接，以及环节4有证据支撑的单文件 HTML 报告（patent-panorama-insights-report），并管理各层之间的检查点、人工标引交接、回滚和进度汇报。
当用户需要基于 PatSnap 或智慧芽专利 MCP/API 数据开展专利全景、专利版图、竞争专利情报、技术路线图、组合规划、产品/R&D 策略项目时使用本技能——无论用户显式调用 /patent-panorama-insights（或…
As a process C 56/100 · 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: 12. 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 56/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 100Tools and files. No external tools needed
- 100Steps. 124 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3585 tokens
- low 16 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 404: enough signal without eating the budget
- +4Structure: 26 headings
- +3Step-by-step instructions: 124 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (9 of 9)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.