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BC polymarket-alpha-suite

6 institutional-grade Polymarket trading tools. NegRisk arbitrage (100% win rate), latency arb, BTC scalping, alpha scanner, universe scanner, edge detection. Battle-tested on 8,347 signals. No Python required.

ClawHub Agent Skills author: aiagent234-bit v1.0.0 MIT-0 12 files body ≈ 2 578 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationInfrastructureSoftware 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
B
82/100
safety, quality, tests
Safety 60%
89
Quality 40%
72
Run on models
none yet
Process rating
C
51/100
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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

Risky intent medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The purpose itself is risky: wallets, browser password stores, offensive security. Even an honest implementation gives the agent access to things that cost money.

For the author

Explain in the description why the access is needed and how it is limited; add tests that show refusals on dangerous requests.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 3

✓ No critical or high findings

Medium and low: 3
  • medium Exfiltration net-credential-use edge_finder.cjs:111
    Credential used in a network call (verify the destination is the intended service)
    const response = await fetch(`${CLOB_BASE}/book?token_id=${tokenId}`);
  • medium Risky intent intent-wallet-secrets skill-card.md:20
    Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target
    Risk: The skill asks for wallet or API credentials for live trading, and the security evidence warns not to use a primary wallet private key. <br>
  • low Dangerous commands cmd-background-process SKILL.md:302
    Starts a background / autostarted process (documentation of a security skill)
    nohup node latency_arb.cjs watch --dry > logs/latency.log 2>&1 &
    security skill

Files scanned: 12. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "acceptLicenseTerms"

Process rating: all ten parameters 51/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 100Steps. 70 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2578 tokens
  • 100Running it twice. Mutating operations check current state
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 12 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
  • +2Single-language instructions
  • +3Description length 210: enough signal without eating the budget
  • +4Structure: 34 headings
  • +3Step-by-step instructions: 70 items
  • +4Has examples (15 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: suspicious
This trading skill mostly scans markets and records paper-trading signals, but it asks for sensitive wallet/API secrets for live trading that the code does not actually implement.
LLM: suspicious (high) · VirusTotal: · 29 May 2026