AD j-patent-strategy-analyzer
Jary66原创，企业战略专利布局分析（模板驱动版）。通过了解企业产品及经营动态与企业全球专利，做对比映射分析。从知产管理视角了解企业的专利布局情况、优势、不足、风险、下一步行动计划等。输出为独立HTML文件（所有CSS和图表内联，零外部依赖）。
Jary66原创，企业战略专利布局分析（模板驱动版）。通过了解企业产品及经营动态与企业全球专利，做对比映射分析。从知产管理视角了解企业的专利布局情况、优势、不足、风险、下一步行动计划等。输出为独立HTML文件（所有CSS和图表内联，零外部依赖）。
As a process D 44/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
AnalyzerSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
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") - 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 (python) that frontmatter does not declare
- 70Execution cost. Instruction body is 4335 tokens
- 100Steps. 71 steps
- 100Consistency. Name and required fields are in place
- 100Running it twice. No mutating operations
- low 13 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 123: enough signal without eating the budget
- +4Structure: 27 headings
- +3Step-by-step instructions: 71 items
- +4Has examples (8 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.
External checks
ClawHub: clean
This skill appears benign: it generates a patent strategy report and clearly discloses its package installation, web/MCP lookups, and checkpoint output files.
LLM: benign (high) · VirusTotal: · 13 Aug 2026