SKILLEMALL.ai

AC multi-city-activation-planner

Plan and price a multi-city event staffing program with one consolidated quote. Use when a user is staffing a tour, roadshow, sampling or mall tour, festival circuit, national brand activation, product-launch rollout, or any program that runs in more than one city, and needs brand ambassadors, registration staff, hospitality, ushers, crowd control, or setup/breakdown crews across several markets at once. Covers matching every city to the configured catalog, planning and pricing each leg with W-2 rate data, surfacing that compliance and overtime differ by state and province, and creating one buyer-operated form handoff so one coordinator can return one quote. Not for a single-city event (use event-staffing-ordering) and not for events outside the US and Canada.

ClawHub Agent Skills author: Megan Hayward v1.7.0 MIT-0 3 files body ≈ 1 845 tokens Open the sourceclawhub.ai analyzed 2 d ago

Plan and price a multi-city event staffing program with one consolidated quote.

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

ProcedureAI and agentsSecurityMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
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: 3. 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
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 5 mutating operations with no state check
    • 40Consistency. Frontmatter name (multi-city-activation-planner) differs from the folder (tempguru-multi-city-activation-planner)
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 100Steps. 9 steps
    • 100Failures and branches. 2 branches, has a failure section
    • 100Execution cost. Instruction body is 1845 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
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 770: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 9 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    This skill is a disclosed TempGuru planning workflow that uses a scoped external MCP service to estimate multi-city event staffing and hand the user to a buyer-operated quote form.
    LLM: benign (high) · VirusTotal: · 14 Aug 2026