SKILLEMALL.ai

BD patent-lifecycle-agent

专利全生命周期管理 Agent V5(授权导向专业版)。从技术交底→布局规划→查新检索→撰写辅助→审查应对→授权维护→侵权监控, 覆盖专利代理人视角下的全周期工作流,融合 Eureka 查新、PatSnap 专利检索、Web Search、 Python附图生成(matplotlib+ezdxf)等能力,生成各阶段专业输出文件。 V5新增:授权导向模式(以下证授权为目标)、OA预案预埋、独权精准化、附图Base64内嵌、 深化检索(6路IPC×关键词系统覆盖)、版本控制。

ClawHub Agent Skills author: yuanzhian-patsnap v1.0.0 MIT-0 2 files body ≈ 2 553 tokens Open the sourceclawhub.ai analyzed 3 d ago

专利全生命周期管理 Agent V5(授权导向专业版)。从技术交底→布局规划→查新检索→撰写辅助→审查应对→授权维护→侵权监控, 覆盖专利代理人视角下的全周期工作流,融合 Eureka 查新、PatSnap 专利检索、Web Search、…

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

ProcedureAI 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%
69
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: 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 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. 110 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2553 tokens
  • 100Running it twice. No mutating operations
  • low 14 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
  • -237 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 238: enough signal without eating the budget
  • +4Structure: 33 headings
  • +3Step-by-step instructions: 110 items
  • +4Has examples (2 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: clean
This skill is a disclosed patent-workflow assistant that uses patent search, web search, file output, and drawing generation in ways that match its stated purpose.
LLM: benign (high) · VirusTotal: · 13 Aug 2026