SKILLEMALL.ai

BD high-value-patent-package

根据用户提供的 PatSnap/智慧芽专利检索式筛选高价值专利包,并生成 HTML 报告(Word 可选)。适用于专利分析师希望按加权指标筛选高价值专利清单的场景:简单同族被引专利数量 30%、简单同族专利数量 30%、核心发明人专利 20%、法律事件历史 20%;输出字段包括公开公告号(链接到智慧芽专利页面)、标题、摘要附图、当前申请(专利权)人、简单法律状态、Patsnap 专利标题、AI 技术三要素和入选理由。

ClawHub Agent Skills author: yuanzhian-patsnap v1.0.0 MIT-0 15 files body ≈ 1 779 tokens Open the sourceclawhub.ai analyzed 3 d ago

根据用户提供的 PatSnap/智慧芽专利检索式筛选高价值专利包,并生成 HTML 报告(Word 可选)。适用于专利分析师希望按加权指标筛选高价值专利清单的场景:简单同族被引专利数量 30%、简单同族专利数量 30%、核心发明人专利 20%、法律事件历史…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationWriting and documentsSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
D
46/100
Unfinished process
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: 15. 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 46/100

  • 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
  • 100Steps. 100 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1779 tokens
  • 100Running it twice. No mutating operations
  • low 11 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
  • -39 of 10 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 210: enough signal without eating the budget
  • +4Structure: 22 headings
  • +3Step-by-step instructions: 100 items
  • +4Has examples (13 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

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

External checks

ClawHub: clean
This skill is a coherent patent-screening workflow that clearly relies on PatSnap/Zhihuiya APIs and local report files, with no evidence of hidden persistence, destructive behavior, or unrelated data access.
LLM: benign (high) · VirusTotal: · 13 Aug 2026