SKILLEMALL.ai

AB objective-evaluator

客观原则评价技能 - Evaluate products, ideas, or designs using objective principles from three design classics. Based on Tony Fadell's Build (painkiller vs vitamin), Don Norman's Design of Everyday Things (three levels of design), and Dieter Rams' Ten Principles (red flags). Use when asked to evaluate, review, critique, judge, or assess any product, service, feature, tool, or design concept objectively. Triggers on phrases like "evaluate this", "what do you think of", "review", "judge", "audit", "评价", "怎么样", or when assessing product-market fit, usability, or design quality.

ClawHub Agent Skills author: JIAWEI YIN v1.0.0 2 files body ≈ 956 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 71/100 · Nearly there — weak spots: inputs and preconditions, running it twice, progress reporting

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
B
71/100
Nearly there
Inputs and preconditions w 11
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: 2. 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 71/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 55Failures and branches. 1 branches
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 23 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 956 tokens

    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

    • +4Description does not say when NOT to use the skill (false activations)
    • -215 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 3 example trigger phrases
    • +3Description length 572: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 23 items
    • +3Output format is stated explicitly
    • +4Has examples (2 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

    External checks

    ClawHub: clean
    This is a markdown-only design evaluation rubric with no code execution, data access, persistence, or hidden behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026