SKILLEMALL.ai

AB map-competitive-patent-landscape-ip

Build an evidence-backed competitive patent landscape for a defined industry, technology, competitor set, geography, and time window. Use when executives, strategy teams, product leaders, competitive-intelligence analysts, or IP teams need to understand competitor technology bets, patent clusters, geographic filing behavior, cross-market differences, representative patents, potential white-space hypotheses, entry timing, and prioritized actions in an accessible HTML report; do not use this skill as an infringement or FTO opinion.

ClawHub Agent Skills author: yuanzhian-patsnap v1.0.0 MIT-0 5 files body ≈ 3 289 tokens Open the sourceclawhub.ai analyzed 3 d ago

Build an evidence-backed competitive patent landscape for a defined industry, technology, competitor set, geography, and time window.

As a process B 66/100 · Nearly there — weak spots: running it twice, progress reporting

GeneratorData and analyticsAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
93
Run on models
none yet
Process rating
B
66/100
Nearly there
Progress reporting w 2
0
Running it twice w 4
30
When it triggers w 12
50
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: 5. 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 66/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 65 steps, 3 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3289 tokens
    • 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
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 535: enough signal without eating the budget
    • +4Structure: 27 headings
    • +3Step-by-step instructions: 65 items
    • +3Output format is stated explicitly
    • +4Reference files are cited in the instructions (2 of 2)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.

    External checks

    ClawHub: clean
    This skill is a disclosed patent-landscape research workflow that uses PatSnap MCP tools and produces an HTML report, with no hidden persistence, exfiltration, or destructive behavior found.
    LLM: benign (high) · VirusTotal: · 13 Aug 2026