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prediction-market-arbitrage

prediction-market-arbitrage is a skill for Claude Code, Codex from AIsa-team/agent-skills. It costs 23 tokens per session (3,804 once invoked), scanned A, original, Apache-2.0.

A tool for comparing prediction markets, which are platforms where people trade contracts tied to future events, such as Polymarket and Kalshi. It finds price differences between matching markets.

In plain words
What is it for?
Use it to match equivalent markets, compare prices, monitor spreads, and inspect order-book depth across supported prediction markets.
Why use it?
It helps identify possible arbitrage: buying related contracts at different prices, while also checking whether market depth makes the difference usable.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: positional $N argument; mentions Claude Code; mentions Codex.

not rated 28repo changed 18d ago A scan SkillSpector: warn 23 tokens original Apache-2.0

Good fit Use it to match equivalent markets, compare prices, monitor spreads, and inspect order-book depth across supported prediction markets.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/aisa-team/agent-skills/prediction-market-arbitrage
View source ↗ AIsa-team/agent-skills
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add AIsa-team/agent-skills --skill prediction-market-arbitrage
Clone the repo
git clone --depth 1 https://github.com/AIsa-team/agent-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for prediction-market-arbitrage

README.md
[![agentmods](https://agentmods.dev/badge/skills/aisa-team/agent-skills/prediction-market-arbitrage/github.svg)](https://agentmods.dev/skills/aisa-team/agent-skills/prediction-market-arbitrage)
Your own site
<a href="https://agentmods.dev/skills/aisa-team/agent-skills/prediction-market-arbitrage"><img src="https://agentmods.dev/badge/skills/aisa-team/agent-skills/prediction-market-arbitrage/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for prediction-market-arbitrage

Your own site · 80×15
<a href="https://agentmods.dev/skills/aisa-team/agent-skills/prediction-market-arbitrage"><img src="https://agentmods.dev/badge/skills/aisa-team/agent-skills/prediction-market-arbitrage.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 23 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,804 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 7 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Data Exfiltration · line 95
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 99
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 107
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 119
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 127
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 139
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 147
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00023 $0.03804
Opus 5.5 $0.00009 $0.01522
Sonnet 5.5 $0.00005 $0.00761
Haiku 4.5 $0.00002 $0.00380

Measured 18d ago against content hash ddb2adcbd5a7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

prediction-market-arbitrage scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 18d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/arbitrage_finder.py, scripts/prediction_market_client.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- curl
financial/prediction-market-arbitrage/SKILL.md · 267 lines

How it starts

The opening of the file, as written. The whole thing — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Cross-Platform Prediction Market Arbitrage ⚖️

AIsa agent rules (shared)

These rules apply to every AIsa-backed skill and are copied from https://aisa.one/llms.txt, the single authoritative agent rule source. When this block and the rest of this skill disagree, follow this block.

Connect (MCP first)

Pick the first option that applies. Run the command yourself; the user only approves the browser sign-in.

  • A. Your client supports remote MCP and can open a browser (default). Add a remote MCP server named AIsa with URL https://mcp.aisa.one/mcp (Streamable HTTP), using your client's own command or config file. Auth: browser OAuth, no key needed. In a chat app (Claude, ChatGPT), the user adds it as a custom connector in settings. Adding the server does not always start sign-in. If no sign-in window opens, start it from the client's own MCP authentication entry (a menu, command, or connector button); if only the user can reach that entry, tell them where it is. Sign-in is the slow step, not the API. Before it starts, tell the user in one line that an AIsa sign-in window or card is about to open and to click Allow (one click if the browser is already signed in to AIsa). Do not call step 2 until the user says sign-in is done or the AIsa tools appear; calling it earlier only returns 401, so do not retry in a loop. If the client must restart to load the server, tell the user and wait. If you cannot add the connector yourself (sandbox, permission denied), give the user the server name and URL above and wait. Do not fall back to another method.
  • B. Your client supports remote MCP but has no browser (CI, SSH, container). Same endpoint, with the header Authorization: Bearer $AISA_API_KEY set in your client's MCP config instead of browser sign-in. If AISA_API_KEY is not set, ask the user to create a key at https://console.aisa.one/api-keys and set it in the environment; never ask them to paste it into chat. Never print, log, or commit the key.
  • C. The client has no MCP support. Use the CLI: npm install -g @aisa-one/cli && aisa login (Node.js 18+). Guide: https://aisa.one/docs/get-started/cli.md
  • D. Calling AIsa over HTTP from your own code. LLMs, OpenAI-compatible: https://api.aisa.one/v1 (Gemini GenerateContent: https://api.aisa.one/v1beta). Data APIs: https://api.aisa.one/apis/v1. Auth: Authorization: Bearer $AISA_API_KEY. Exact paths and schemas: https://aisa.one/docs/api-reference

Read the full file on GitHub · 267 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 18d ago Changed · +65 lines ddb2adcbd5a7
  2. 25d ago Changed · +1 lines d102ccb45ca4
  3. 2mo ago First seen · 201 lines · 23 tokens per session scan A c75574b4b44b

Subscribe to this mod's changes

prediction-market-arbitrage is a skill published in the GitHub repository AIsa-team/agent-skills (28 stars, last pushed yesterday), licensed Apache-2.0. It adds 23 tokens to every session and 3,804 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Finance and fintech
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prediction-market-arbitrage next to 6 skills from other repositories
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prediction-market-arbitrageAIsa-team/agent-skillsSkill28yesterdayApache-2.0A23Claude Code, Codex
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airdrop-hunting-guidenirholas/three.wsSkill269yesterdayApache-2.0A54Claude Code, Codex
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