SKILLEMALL.ai

AC quakeproof

Look up every recent earthquake near a SPECIFIC U.S. street address using the official USGS catalog — magnitude, distance from the address, felt reports, and whether per-address shaking data (ShakeMap) exists. Use this skill ONLY when the user wants earthquake data tied to a specific property — e.g. "did the June quake shake my house at [address]", "USGS data for my earthquake claim", "how strong was Ridgecrest at [address]", "earthquake history for a property I'm buying". The tell is an address (or intent to provide one) plus a verification purpose: an insurance claim (CEA or private), a "those cracks were pre-existing" dispute, a FEMA Individual Assistance or SBA disaster loan application, California property-tax reassessment after quake damage, or real-estate due diligence. Do NOT activate for general earthquake news, seismology curiosity, prediction questions, or named-quake questions that aren't about a specific property.

ClawHub Agent Skills author: Oasis Engineering v1.0.1 MIT-0 2 files body ≈ 4 557 tokens Open the sourceclawhub.ai analyzed 21 h ago

Look up every recent earthquake near a SPECIFIC U.S. street address using the official USGS catalog — magnitude, distance from the address, felt reports, and…

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

ProcedureData and analyticsWriting and documentsFinancetype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
C
63/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
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: 0. 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

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 7 mutating operations with no state check
    • 65Failures and branches. 3 branches
    • 70When it triggers. States when to use, but not when not to
    • 70Execution cost. Instruction body is 4557 tokens
    • 100Tools and files. No external tools needed
    • 100Steps. 53 steps
    • 100Consistency. Name and required fields are in place
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 11 top-level sections: this looks like several domains in one skill

    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)
    • +3Description length 940: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 5 example trigger phrases
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 53 items
    • +4Has examples (3 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: clean
    This skill is a clearly scoped earthquake lookup that discloses its third-party address lookup and requires user consent before sending data.
    LLM: benign (high) · VirusTotal: · 5 Aug 2026