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AC polymarket-arbitrage

Monitor and execute arbitrage opportunities on Polymarket prediction markets. Detects math arbitrage (multi-outcome probability mismatches), cross-market arbitrage (same event different prices), and orderbook inefficiencies. Use when user wants to find or trade Polymarket arbitrage, monitor prediction markets for opportunities, or implement automated trading strategies. Includes risk management, P&L tracking, and alerting.

ClawHub Agent Skills author: JohnY0920 v0.1.0 11 files body ≈ 1 554 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerInfrastructureFinancetype 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
96/100
safety, quality, tests
Safety 60%
99
Quality 40%
91
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Exfiltration exfil-webhook-url SKILL.md:216
      Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
      python scripts/monitor.py --alert-webhook "https://api.telegram.org/bot<token>/sendMessage?chat_id=<id>"
      placeholder

    Files scanned: 11. 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 54/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 20When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Failures and branches. 2 branches
    • 100Steps. 68 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1554 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • 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

    • +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 426: enough signal without eating the budget
    • +4Structure: 33 headings
    • +3Step-by-step instructions: 68 items
    • +4Has examples (6 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +3All 3 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

    External checks

    ClawHub: suspicious
    This skill is a Polymarket market scanner, but it overstates trading capabilities and contains unsafe command execution and credential-handling patterns users should review before installing.
    LLM: suspicious (high) · VirusTotal: benign · 10 Sept 2026