Nansen

Tracking Smart Money perp trades

smart_traders_and_funds_perp_trades

Get recent Hyperliquid perpetual futures trades from Smart Money addresses across all tokens.

Optional labels narrow this cohort; they do not search all addresses with that label. For a broad view of Smart Money activity across all tokens, use token_discovery_screener with traderType="sm".

Note: This endpoint is Hyperliquid-only (perpetual futures data). It returns recent trades only (no date filtering available).

Columns returned:

Time: Timestamp when the trade occurred (datetime: YYYY-MM-DD HH:MM:SS)
Side: Position direction - Long or Short
Action: Order action - Add, Reduce, Open, Close
Token: Symbol of the perpetual contract
Size: Quantity of the perpetual contract (numeric)
Price USD: Price per token at time of trade (price formatted)
Value USD: Total USD value of the trade (currency formatted)
Trader: Nansen label of the trading address
Address: Full trading wallet address
Tx Hash: Blockchain transaction hash for verification

Sorting Options (all fields support "asc"/"desc"): Available for sorting: timestamp, amount, price_usd

Examples: # Get recent smart money perp trades (sorted by amount) { "orderBy": "amount", "order_by_direction": "desc" }

# Filter by action and side
```
{
  "action": "Open",
  "side": "Long"
}
```

Input Schema

TableJSON Schema

Name	Required	Description	Default
`request`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.3/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full responsibility, and it delivers: it clarifies Hyperliquid-only perpepetual data, recency of data, no-date-filtering, cohort-narrowing semantics, and a detailed column contract. It could add pagination/latency details, but this is generally strong for agent decision-making.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with a lead positional summary, bolded leave item, sorting options, and code examples. Mostly efficient and each section earns its place, though the column list is verbose and redundant to the schema names—but it is justified because there is no output schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema, this description provides the returned columns, sorting rule, filtering via action/side, and an alternative for broad Smart Money discovery. It is complete enough to call correctly for most flows, though it doesn't mention pagination limits or page semantics beyond the schema default.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although the schema contains property-level descriptions, the tool description adds meaning by giving concrete examples for orderBy+order_by_direction + action+side filtering, listing sortable fields, and explaining which labels can be used. It does not rename every parameter, but it compensates well. Given the stated schema_description_coverage of 0%, this is very helpful in practice.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description has a specific verb-resource combination: 'Get recent Hyperliquid perpetual futures trades from Smart Money addresses across all tokens.' It makes the perp contract scope explicit and the note on optional labels distingishes it from generic address-label lookups. The tool is clearly differentiated among siblings like token_dex_trades and prediction_market_trades.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly routes the agent to a alternative when broad Smart Money activity is needed: token_discovery_screener with traderType="sm". It also provides situational guidance via 'recommend-only, no date-filtering' and the note that labels narrow a fixed cohort rather than searching all labeled addresses. Missing explicit when-not-to-use for the other sibling tools, so not a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.8/5.0

Disambiguation5/5

Each tool has a clearly defined purpose, and overlapping tools (e.g., token_flows vs token_recent_flows_summary, nansen_score_top_tokens vs token_discovery_screener) include explicit guidance on when to use them. Even with similar names like prediction_market_trades and prediction_market_address_trades, the descriptions and parameters make the distinction unambiguous.

Naming Consistency4/5

Most tools follow a domain_prefix_noun pattern (address_, token_, prediction_market_), making them predictable within families. However, outliers like general_search, growth_chain_rank, hyperliquid_leaderboard, and transaction_lookup break the pattern, and some names are long or inconsistently formatted (e.g., smart_traders_and_funds_perp_trades vs smart_traders_and_funds_token_balances).

Tool Count3/5

With 38 tools, the server is far above the typical 3-15 range, making it heavy for agents to navigate. However, Nansen is a broad analytics platform covering wallets, tokens, prediction markets, and smart money activity, so the high count is justifiable as each tool serves a distinct function.

Completeness5/5

The tool set provides comprehensive coverage across token analysis (ohlcv, trading, holders, flows, PnL, technicals), wallet analysis (portfolio, transactions, counterparties), prediction markets (lookup, orderbook, trades, PnL), and discovery. The only obvious omission is NFT support, but it is explicitly documented as out of scope, so no critical dead ends exist.

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