SKILLEMALL.ai
GitHub ↗ RU Sign in

BF generic-fto-report

根据风险点 Word 文档和用户提供的 PatSnap 检索式生成通用行业专利 FTO 报告。适用于专利风险分析师提供目标产品/技术特征及一个或多个直接检索式，并希望 Codex 执行 P002 专利检索、用 P018 获取权利要求 1、运行 AI07 辅助侵权比对，并输出可追溯 FTO 报告的场景。

ClawHub Agent Skills author: yuanzhian-patsnap v1.0.0 MIT-0 12 files body ≈ 1 208 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

根据风险点 Word 文档和用户提供的 PatSnap 检索式生成通用行业专利 FTO 报告。适用于专利风险分析师提供目标产品/技术特征及一个或多个直接检索式，并希望 Codex 执行 P002 专利检索、用 P018 获取权利要求 1、运行 AI07 辅助侵权比对，并输出可追溯 FTO 报告的场景。

As a process F 35/100 · Will not run — References files that are not bundled: assets/FTO报告模板.docx

IntegrationWordSoftware developmentData and analyticstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
99
Quality 40%
72
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: assets/FTO报告模板.docx
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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.
  2. The text references files that are not there: add them or drop the references.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-password-literal scripts/zhihuiya_api.py:85
    Hard-coded password / key literal (may be an example) (quoted — discussed, not commanded)
    client_secret : P002/P070/P018 OAuth 用的 Client Secret
    quoted

Files scanned: 12. 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")
  • warning missing-ref reference to a missing file: assets/FTO报告模板.docx
  • note frontmatter-key unknown frontmatter key "copyright"

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: assets/FTO报告模板.docx
  • 0Tools and files. 1 referenced file(s) missing: assets/FTO报告模板.docx
  • 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
  • 100Steps. 62 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1208 tokens
  • 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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 151: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 62 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (3 of 4)
  • +3All 3 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: suspicious
The skill matches its patent FTO purpose, but its external API/AI data flows and MCP setup are inconsistent enough that users should review it carefully before installing.
LLM: suspicious (high) · 13 Aug 2026