SKILLEMALL.ai

AB user-research-synthesis

Use this skill when a UX researcher or product team has raw qualitative data — transcripts, usability notes, survey responses, or diary entries — and needs a structured insights report. Produces evidence-backed themes and recommendations a product team can act on.

ClawHub Agent Skills author: devasher v0.2.2 MIT-0 4 files body ≈ 1 960 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 69/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, running it twice

GeneratorData and analyticsInfrastructureDesigntype 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
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
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: 4. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 69/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Steps. 15 steps
    • 100Failures and branches. 6 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1960 tokens
    • 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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 264: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 15 items
    • +3Output format is stated explicitly
    • +4Has examples (4 code blocks)

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

    External checks

    ClawHub: clean
    This skill is a disclosed UX research synthesis workflow that asks for user-provided research data and turns it into anonymized, evidence-backed reports.
    LLM: benign (high) · VirusTotal: · 28 May 2026