SKILLEMALL.ai

AB signaling-games

Activate when: user asks 'how do we prove we're high quality when they can't verify it', 'what credential or signal would work here', 'why is everyone spending so much on brand advertising', 'how do we tell who's the real one among these candidates', 'cheap talk isn't working — we need something credible', or describes a market where one side can't verify the other's quality/intentions/type (hiring, fundraising, B2B procurement, branding, M&A due diligence). Do NOT activate when: information is fully symmetric and both parties already know the relevant facts; or the question is about game theory in general without an information asymmetry component. More: deciqai.com/c/signaling-games

ClawHub Agent Skills author: deciqAI v1.0.4 MIT-0 5 files body ≈ 2 115 tokens Open the sourceclawhub.ai analyzed 2 d ago

Activate when: user asks 'how do we prove we're high quality when they can't verify it', 'what credential or signal would work here', 'why is everyone…

As a process B 65/100 · Nearly there — weak spots: inputs and preconditions, failures and branches, running it twice

ProcedureMarketingPeople and hiringtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
91
Run on models
none yet
Process rating
B
65/100
Nearly there
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: 5. 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 65/100

    • 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. 11 mutating operations with no state check
    • 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. 39 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2115 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
    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +3Description length 693: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 39 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: 91.

    External checks

    ClawHub: clean
    This is a markdown-only educational skill for applying signaling-game analysis, with no executable code, persistence, credential access, or hidden authority.
    LLM: benign (high) · VirusTotal: · 17 Jul 2026