SKILLEMALL.ai

AB create-patent-based-rd-briefing-rd

Create an evidence-bounded English patent-based R&D briefing from an authorized Excel workbook. Use when a user supplies patent records and asks to screen relevance, organize reviewed records by technology route and organization, preserve approved workbook links or figures, and generate a self-contained scientific HTML briefing with reproducible scope, review provenance, and patent-professional boundaries.

ClawHub Agent Skills author: yuanzhian-patsnap v1.0.0 MIT-0 17 files · 2 scripts body ≈ 4 286 tokens Open the sourceclawhub.ai analyzed 3 d ago

Create an evidence-bounded English patent-based R&D briefing from an authorized Excel workbook.

As a process B 69/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting

GeneratorExcelData and analyticsAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
B
69/100
Nearly there
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: 17. 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 69/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 9 mutating operations with no state check
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Execution cost. Instruction body is 4286 tokens
    • 100Steps. 207 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 1 branches, has a failure section
    • 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 22 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
    • +2Single-language instructions
    • +3Description length 409: enough signal without eating the budget
    • +4Structure: 37 headings
    • +3Step-by-step instructions: 207 items
    • +4Has examples (5 code blocks)
    • +3All 3 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: clean
    This skill is a coherent local patent-workbook reporting tool with expected file processing behavior and no evidence of hidden network access, credential use, or destructive actions.
    LLM: benign (high) · VirusTotal: · 13 Aug 2026