SKILLEMALL.ai

AC multi-patent-avoidance

多专利规避方法论(8步法)——同时规避N件风险专利(N≥2)的应用驱动型FTO分析流程。 本技能嵌套调用 application-requirements-card(前置)+ patent-avoidance-design(深度规避主要风险专利)两个子技能, 通过"应用需求驱动+情报矩阵+安全区识别+交叉扫描+定向修复"实现多专利联合规避。 触发词包括:"多专利规避"、"FTO"、"自由实施分析"、"规避多个专利"、"专利风险地图"、"专利组合规避"。 本技能产出:FTO安全区图谱、配方/方案候选、交叉扫描矩阵、风险修复版方案、FTO意见书框架。

ClawHub Agent Skills author: yuanzhian-patsnap v1.0.0 MIT-0 2 files body ≈ 2 221 tokens Open the sourceclawhub.ai analyzed 2 d ago

多专利规避方法论(8步法)——同时规避N件风险专利(N≥2)的应用驱动型FTO分析流程。 本技能嵌套调用 application-requirements-card(前置)+ patent-avoidance-design(深度规避主要风险专利)两个子技能,…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentsWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. 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-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "copyright"

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 115 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2221 tokens
  • 100Running it twice. No mutating operations
  • 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

  • +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
  • +5Description quotes 5 example trigger phrases
  • +3Description length 276: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 115 items
  • +4Has examples (8 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: clean
This is a disclosed Chinese-language patent FTO/design-around workflow with no executable code, persistence, or hidden data handling, though users should treat its legal outputs as draft analysis only.
LLM: benign (high) · VirusTotal: · 13 Aug 2026