SKILLEMALL.ai

AC disease-investigation

Conduct comprehensive disease investigation combining academic literature, epidemiological data, clinical guidelines, pharmaceutical intelligence, and clinical trial reports. Users may inquire about disease pathogenesis, symptoms, pharmaceutical interventions, treatment options, patent landscapes, and business development opportunities. Load the skill when queries involve: - Disease pathology and molecular mechanisms - Regional disease incidence and subtypes - Clinical symptoms and diagnostic indicators - Treatment landscape and drug development pipeline - Patent and IP analysis for therapeutic areas - Business development and deal intelligence Typical queries - Pathogenesis of NSCLC - Treatment options for influenza - Incidence rates of leukemia in China - Clinical manifestations of depression - PD-1/PD-L1 patent landscape - Drug development pipeline for NSCLC

ClawHub Agent Skills author: yuanzhian-patsnap v1.0.1 MIT-0 2 files body ≈ 3 451 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process C 62/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
C
62/100
Has gaps
Inputs and preconditions w 11
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: disease-investigation (ClawHub)

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: 2. 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 62/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 85Steps. 70 steps, 2 vague phrases
    • 100Failures and branches. 3 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3451 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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)
    • +3Description length 875: 120–800 characters recommended
    • +2Single-language instructions
    • +4Structure: 24 headings
    • +3Step-by-step instructions: 70 items
    • +3Output format is stated explicitly
    • +4Has examples (6 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    This skill is a disclosed PatSnap life-science research workflow that requires a user-configured MCP service and does not include hidden code, destructive actions, or unrelated data access.
    LLM: benign (high) · VirusTotal: · 13 Aug 2026