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 agentmods add skills/nansen-ai/nansen-cli/nansen-token-transfer-analysisnpx skills add nansen-ai/nansen-cli --skill nansen-token-transfer-analysisgit 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-token-transfer-analysis)<a href="https://agentmods.dev/skills/nansen-ai/nansen-cli/nansen-token-transfer-analysis"><img src="https://agentmods.dev/badge/skills/nansen-ai/nansen-cli/nansen-token-transfer-analysis.svg" alt="Measured on agentmods" 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 | $0.00028 | $0.00417 |
| Opus 5 | $0.00014 | $0.00209 |
| Sonnet 5 | $0.00006 | $0.00083 |
| Haiku 4.5 | $0.00003 | $0.00042 |
Grade A, and why
nansen-token-transfer-analysis 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 6d 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
Token Forensics
Answers: "Where is this token moving? Who is sending it and where?"
TOKEN=<address> CHAIN=ethereum
# Examples: UNI on ethereum (0x1f9840a85d5aF5bf1D1762F925BDADdC4201F984)
# BONK on solana (DezXAZ8z7PnrnRJjz3wXBoRgixCa6xjnB7YaB1pPB263)
# Note: token flows does NOT support stablecoins (USDC, USDT, etc.) — use non-stablecoin tokens
nansen research token transfers --token $TOKEN --chain $CHAIN --days 7 --limit 20
# → from_address_label, to_address_label, transfer_amount, transfer_value_usd
nansen research token flows --token $TOKEN --chain $CHAIN --days 7 --limit 20
# → date, price_usd, holders_count, total_inflows_count, total_outflows_count
# ⚠ Returns HTTP 422 for stablecoins — skip this command if TOKEN is a stablecoin
nansen research token flow-intelligence --token $TOKEN --chain $CHAIN
# → net_flow_usd per label: smart_trader, whale, exchange, fresh_wallets, public_figure
Rising exchange_net_flow + large transfers to exchange addresses = potential sell pressure. Fresh wallet inflows may signal new interest or wash trading.
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.
- 6d ago First seen · 41 lines · 28 tokens per session scan A 7c24a021f585
nansen-token-transfer-analysis is a skill published in the GitHub repository nansen-ai/nansen-cli (134 stars, last pushed today), licensed MIT. It adds 28 tokens to every session and 417 once invoked, about $0.0001 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.
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