SKILLEMALL.ai

AC survivorship-bias

Activate when: user says 'look at what winners/billionaires/champions did,' investment returns or fund performance are being cited, a strategy is justified by pointing to companies that succeeded, historical data is treated as representative of all cases, or someone says 'this works because X did it.' Do NOT activate when: population data is available and already selection-corrected; analysis is explicitly about survivors only with no claim about the broader population. More: deciqai.com/c/survivorship-bias

ClawHub Agent Skills author: deciqAI v1.0.5 MIT-0 6 files body ≈ 1 657 tokens Open the sourceclawhub.ai analyzed 2 d ago

Activate when: user says 'look at what winners/billionaires/champions did,' investment returns or fund performance are being cited, a strategy is justified by…

As a process C 63/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, running it twice

ProcedureData and analyticsLearningtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
95
Run on models
none yet
Process rating
C
63/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
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: 6. 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 63/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 6 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Steps. 22 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1657 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 512: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 22 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 95.

    External checks

    ClawHub: clean
    This is a benign educational reasoning skill with no executable code; the only caution is a note that could be read as saving observed examples after use.
    LLM: benign (high) · VirusTotal: · 17 Jul 2026