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 nansen-ai/nansen-cli --skill nansen-prediction-marketsgit clone --depth 1 https://github.com/nansen-ai/nansen-cliWrote 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/nansen-ai/nansen-cli/nansen-prediction-markets)<a href="https://agentmods.dev/skills/nansen-ai/nansen-cli/nansen-prediction-markets"><img src="https://agentmods.dev/badge/skills/nansen-ai/nansen-cli/nansen-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/nansen-ai/nansen-cli/nansen-prediction-markets"><img src="https://agentmods.dev/badge/skills/nansen-ai/nansen-cli/nansen-prediction-markets.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket warn
- Snyk warn
- NVIDIA SkillSpector pass
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 | $0.00038 | $0.00427 |
| Opus 5 | $0.00019 | $0.00214 |
| Sonnet 5 | $0.00008 | $0.00085 |
| Haiku 4.5 | $0.00004 | $0.00043 |
Grade A, and why
nansen-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 10d 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 Market Screeners
All commands: nansen research prediction-market <sub> [options] (alias: nansen research pm <sub>)
No --chain flag needed — Polymarket runs on Polygon.
# Top events (groups of related markets)
nansen research pm event-screener --sort-by volume_24hr --limit 20
# → event_title, market_count, total_volume, total_volume_24hr, total_liquidity, total_open_interest, tags
# Top markets by 24h volume
nansen research pm market-screener --sort-by volume_24hr --limit 20
# → market_id, question, best_bid, best_ask, volume_24hr, liquidity, open_interest, unique_traders_24h
# Search for specific markets
nansen research pm market-screener --query "bitcoin" --limit 10
# Find resolved/closed markets
nansen research pm market-screener --status closed --limit 10
# Browse categories
nansen research pm categories --pretty
# → category, active_markets, total_volume_24hr, total_open_interest
Sort options: volume_24hr, volume, volume_1wk, volume_1mo, liquidity, open_interest, unique_traders_24h, age_hours
Screeners return active/open markets by default. Use --status closed for resolved markets.
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.
- 10d ago First seen · 48 lines · 38 tokens per session scan A c64fb26a6f6b
nansen-prediction-markets is a skill published in the GitHub repository nansen-ai/nansen-cli (135 stars, last pushed today), licensed MIT. It adds 38 tokens to every session and 427 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 2026-08-30.
Other skills, from other repositories
sector-rotation
An analysis framework for comparing industries in the Chinese A-share stock market, using business conditions, price momentum, valuation, and money flows. It produces rankings and higher- or lower-allocation suggestions.
strategy-pivot-designer
Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.
twitter-reader
Read Twitter/X for financial research using opencli (read-only). Use this skill whenever the user wants to read their Twitter feed, search for financial tweets, view bookmarks, look up user profiles, or gather market sentiment from Twitter/X. Triggers include: "check my feed", "search Twitter for", "show my…
chenhao-limit-up
A framework for judging Chinese A-share stocks that have reached the daily price-rise limit, using market mood, sector leadership, and trading momentum.
trading-risk-gate
Unified pre-trade safety gate: Ruin check (Law #1), ergodicity audit, and win-rate dominance validation. Absorbs: ergodicity-check, law-of-ruin, win-rate-dominance.
vectorbt
High-performance vectorized backtesting with parameter optimization, portfolio simulation, and rich performance metrics.