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AB LocalSquare: Claim Local Business Ads via AI Agent

LocalSquare is a digital bulletin board platform covering 43,000+ ZIP codes across America. Local businesses claim squares on their town's 10x10 grid, getting a dedicated SEO-optimized webpage that...

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 4 001 tokens Open the sourcegithub.com↗ analyzed 4 d ago

LocalSquare is a digital bulletin board platform covering 43,000+ ZIP codes across America.

As a process B 65/100 · Nearly there — weak spots: result and completion, inputs and preconditions, consistency

ProcedureAI and agentsSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
B
65/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
0
Consistency w 8
40
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: 1. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)

    Process rating: all ten parameters 65/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 40Consistency. Frontmatter name (LocalSquare: Claim Local Business Ads via AI Agent) differs from the folder (localsquare-ads)
    • 70When it triggers. States when to use, but not when not to
    • 70Execution cost. Instruction body is 4001 tokens
    • 100Tools and files. No external tools needed
    • 100Steps. 64 steps
    • 100Failures and branches. 3 branches, has a failure section
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 13 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 200: enough signal without eating the budget
    • +4Structure: 27 headings
    • +3Step-by-step instructions: 64 items
    • +4Has examples (10 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.