SKILLEMALL.ai

BC patent-pre-evaluation-report

根据技术方案、交底书草稿、发明构思或既有报告,创建并迭代完善中文专利申请前预评估报告。适用于用户要求专利申请前预评估、专利预评估报告、查新点提炼、可专利性分析、非正常申请风险排查、申请策略建议,或基于 PatSnap/智慧芽检索证据更新报告的场景。

ClawHub Agent Skills author: yuanzhian-patsnap v1.0.0 MIT-0 4 files body ≈ 1 694 tokens Open the sourceclawhub.ai analyzed 3 d ago

根据技术方案、交底书草稿、发明构思或既有报告,创建并迭代完善中文专利申请前预评估报告。适用于用户要求专利申请前预评估、专利预评估报告、查新点提炼、可专利性分析、非正常申请风险排查、申请策略建议,或基于 PatSnap/智慧芽检索证据更新报告的场景。

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
C
51/100
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: 4. 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 51/100

  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 100Tools and files. No external tools needed
  • 100Steps. 105 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1694 tokens

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
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 124: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 105 items
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: clean
This is a coherent patent pre-evaluation report skill that uses disclosed PatSnap MCP searches and writes a local HTML report, with credential-handling caveats for users.
LLM: benign (high) · VirusTotal: · 13 Aug 2026