SKILLEMALL.ai

AC assess-high-value-patent-portfolio-ip

Rank a user-defined PatSnap patent candidate universe with an auditable 30/30/20/20 model based on simple-family forward citations, simple-family size, core-inventor concentration, and verified legal-event activity; select a documented 10–15% screening portfolio and generate traceable English HTML, JSON, and optional Word outputs. Use for evidence-based patent portfolio triage, high-value patent screening, candidate prioritization, or portfolio-review preparation—not monetary valuation, validity, enforceability, or investment conclusions.

ClawHub Agent Skills author: yuanzhian-patsnap v1.0.0 MIT-0 15 files body ≈ 4 885 tokens Open the sourceclawhub.ai analyzed 3 d ago

Rank a user-defined PatSnap patent candidate universe with an auditable 30/30/20/20 model based on simple-family forward citations, simple-family size…

As a process C 64/100 · Has gaps — weak spots: result and completion, running it twice, progress reporting

AnalyzerResearchFinanceData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
C
64/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

    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

    • note frontmatter-key unknown frontmatter key "copyright"

    Process rating: all ten parameters 64/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Execution cost. Instruction body is 4885 tokens
    • 100Steps. 155 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 15 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
    • +3Output format is not stated: the model decides each time
    • -35 of 10 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 544: enough signal without eating the budget
    • +4Structure: 28 headings
    • +3Step-by-step instructions: 155 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: clean
    This skill is a disclosed PatSnap patent-screening workflow with a bounded optional image-fetching feature users should enable carefully.
    LLM: benign (high) · VirusTotal: · 13 Aug 2026