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.
npx skills add DanielTomaro13/sportsdata-agents --skill prediction_marketsgit clone --depth 1 https://github.com/DanielTomaro13/sportsdata-agentsWrote 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.
[](https://agentmods.dev/skills/danieltomaro13/sportsdata-agents/prediction_markets)<a href="https://agentmods.dev/skills/danieltomaro13/sportsdata-agents/prediction_markets"><img src="https://agentmods.dev/badge/skills/danieltomaro13/sportsdata-agents/prediction_markets/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.
<a href="https://agentmods.dev/skills/danieltomaro13/sportsdata-agents/prediction_markets"><img src="https://agentmods.dev/badge/skills/danieltomaro13/sportsdata-agents/prediction_markets.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00043 | $0.00472 |
| Opus 5 | $0.00022 | $0.00236 |
| Sonnet 5 | $0.00009 | $0.00094 |
| Haiku 4.5 | $0.00004 | $0.00047 |
Grade A, and why
prediction_markets scanned grade A with 0 findings 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 11d ago.
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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Prediction markets
Prediction markets (Kalshi, Polymarket) trade binary/event contracts that pay 1 unit if an outcome happens and 0 if it doesn't. The contract's price therefore is the market's probability: a contract trading at 0.62 means a 62% implied chance.
Read the resolution rules first
The single biggest mistake is comparing two markets that resolve differently. Before
any comparison, read market_detail for the exact question, the settlement source,
and the expiry. "Team X wins the title" and "Team X wins the final" are different
contracts. If the book's market and the prediction market don't resolve on the same
condition, say so and stop — the comparison is invalid.
Price → probability
- Best bid / best ask (
market_prices) bracket the fair value; use the mid for a point estimate and note the spread (wide spread = thin/uncertain market). - Do not vig-remove a single binary contract price — it's already a probability. The exchange takes a fee on settlement, not a two-sided overround like a book.
The exchange-vs-book edge
This is the high-value play and why this agent exists:
- Take the contract's implied probability (prediction market).
- Take the SAME outcome at the sportsbooks (
find_fixture→best_prices), andvig_removalthe book market to a fair probability. - Compare. A meaningful gap means one side is mispriced relative to the other — report which side is the value, the size of the gap, and the venues. Liquidity and the fee/withdrawal frictions on each venue determine whether it's actually takeable.
Honesty
Surface the probabilities, the gap, and the caveats (thin liquidity, resolution-rule mismatch, fees). The user decides and acts; this agent never trades or bets.
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.
- 11d ago First seen · 37 lines · 43 tokens per session scan A 588af2398fc5
prediction_markets is a skill published in the GitHub repository DanielTomaro13/sportsdata-agents (5 stars, last pushed 8d ago), licensed MIT. It adds 43 tokens to every session and 472 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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