SKILLEMALL.ai

AC party-guest-optimizer

Use when planning a party or dinner and the GUEST LIST is the hard part - who to invite together, who to keep apart, how to seat them, and how to grow a network of strangers into friends. Guest-graph analysis, invite scenarios, and seating charts that maximize spark and minimize clash.

ClawHub Agent Skills author: voronindenis5 v1.0.0 MIT-0 7 files · 2 scripts body ≈ 1 832 tokens Open the sourceclawhub.ai↗ analyzed 16 d ago

Use when planning a party or dinner and the GUEST LIST is the hard part - who to invite together, who to keep apart, how to seat them, and how to grow a…

As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

ProcedureAI and agentstype 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
C
52/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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: 7. 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 52/100

    • 0Result and completion. Does not say what the result is
    • 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. 1 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 85Steps. 26 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1832 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
    • +3Output format is not stated: the model decides each time
    • -31 of 2 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 286: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 26 items
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +1License stated

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

    External checks

    ClawHub: clean
    This is a local party-planning helper whose relationship-sensitive output is expected for its purpose, with no evidence of hidden network access, credential use, or persistence.
    LLM: benign (high) · VirusTotal: · 28 Sept 2026