nansen-token-screener

nansen-token-screener is a skill for Claude Code from nansen-ai/nansen-cli. It costs 39 tokens per session (1,951 once invoked), scanned A, original, MIT.

A Solana token-screening tool for finding tokens with high activity, smart-money interest, and notable market signals. Solana is a blockchain network, and smart money means wallets identified as skilled or influential traders.

In plain words
What is it for?
Use it to list trending tokens, filter results, see what labelled smart-money wallets hold, inspect a token’s risk and reward indicators, and review money moving into or out of it.
Why use it?
It reduces the need to check token volume, liquidity, holdings, risk signals, and money flows separately when looking for tokens to investigate.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: built for openclaw.

not rated 135repo +2 today A scan Socket: passSnyk: passSkillSpector: pass 39 tokens original MIT

Good fit Use it to list trending tokens, filter results, see what labelled smart-money wallets hold, inspect a token’s risk and reward indicators, and review money moving into or out of it.

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Install with agentmods
npx agentmods add skills/nansen-ai/nansen-cli/nansen-token-screener
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 nansen-ai/nansen-cli --skill nansen-token-screener
Clone the repo
git clone --depth 1 https://github.com/nansen-ai/nansen-cli

Made for: Claude Code.

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 nansen-token-screener

README.md
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Your own site
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Your own site · 80×15
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Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,951 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 24 Apr 2026
  • Snyk pass 24 Apr 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
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 $0.00039 $0.01951
Opus 5 $0.00019 $0.00975
Sonnet 5 $0.00008 $0.00390
Haiku 4.5 $0.00004 $0.00195

Measured 10d ago against content hash 59f4f6f0d7dd, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

nansen-token-screener 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.

skills/nansen-token-screener/SKILL.md · 109 lines

How it starts

The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Token Discovery

Answers: "What tokens are trending and worth a deeper look?"

CHAIN=solana

# Screen top tokens by volume
nansen research token screener --chain $CHAIN --timeframe 24h --limit 20
# → token_symbol, price_usd, price_change, volume, buy_volume, market_cap_usd, fdv, liquidity, token_age_days

# Smart money only
nansen research token screener --chain $CHAIN --timeframe 24h --smart-money --limit 20

# Search within screener results (client-side filter)
nansen research token screener --chain $CHAIN --search "bonk"

# Smart money holdings — what SM wallets are holding
nansen research smart-money holdings --chain $CHAIN --labels "Smart Trader" --limit 20
# → token_symbol, value_usd, holders_count, balance_24h_percent_change, share_of_holdings_percent

# Nansen indicators for a specific token
TOKEN=<address>
nansen research token indicators --token $TOKEN --chain $CHAIN
# → risk_indicators, reward_indicators (each with score, signal, signal_percentile)

# Flow intelligence — only use for promising tokens from screener/indicators above
nansen research token flow-intelligence --token $TOKEN --chain $CHAIN
# → net_flow_usd per label: smart_trader, whale, exchange, fresh_wallets, public_figure

# Nansen Score Top Tokens — "what should I buy?" (public endpoint, any authenticated API key)
# Use this FIRST for discovery, then drill into individual tokens with `indicators` above
nansen research token top-tokens --limit 25
nansen research token top-tokens --market-cap largecap --limit 10
# → chain, token_address, token_symbol, performance_score, risk_score,
#   per-indicator contributions, market_cap_group, latest_date, last_trigger_on

Screener timeframes: 5m, 10m, 1h, 6h, 24h, 7d, 30d

Indicators: score is "bullish"/"bearish"/"neutral". signal_percentile > 70 = historically significant. Some tokens return empty indicators — not an error.

Top tokens — Nansen Score field reference

Results are pre-filtered to performance_score >= 15 server-side and returned sorted by:

  1. performance_score DESC
  2. market_cap_group priority (largecap → midcap → lowcap)
  3. risk_score DESC
  4. 24h volume DESC

Read the full file on GitHub · 109 lines

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. 10d ago First seen · 109 lines · 39 tokens per session scan A 59f4f6f0d7dd

Subscribe to this mod's changes

nansen-token-screener is a skill published in the GitHub repository nansen-ai/nansen-cli (135 stars, last pushed today), licensed MIT. It adds 39 tokens to every session and 1,951 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.