Nansen

Finding recent traders

token_who_bought_sold

Get TOTAL amount of tokens bought/sold by address for a token on DEX (Decentralised Exchanges) ONLY.

Use this tool to find out WHO is buying or selling a token (on DEX) AND then you can check if they are liquidating profits or accumulating more.

Returns: Aggregated buyer/seller activity as markdown. Returns empty string if no trading data found.

Columns returned:
- **Address**: Trader's wallet address
- **Label**: Nansen label of the address
- **Bought Token Volume**: Total quantity of tokens purchased
- **Sold Token Volume**: Total quantity of tokens sold
- **Gross Token Volume**: Combined buy and sell volume in tokens
- **Bought Volume USD**: USD value of all token purchases
- **Sold Volume USD**: USD value of all token sales
- **Gross Volume USD**: Combined USD trading volume

Sorting Options: You can sort asc or desc by bought_volume_usd or sold_volume_usd

Notes: - buy_or_sell parameter filters for "BUY" (net buyers) or "SELL" (net sellers) - Aggregates all trading activity within the specified time range

Input Schema

TableJSON Schema

Name	Required	Description	Default
`request`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.1/5.0

Behavior5/5

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

With no annotations, the description fully carries the burden and does well. It discloses return format (markdown), empty-string behavior, aggregation over time range, DEX-only scope, and filtering semantics. This goes beyond basic schema information and gives the agent a clear picture of what to expect.

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?

The description is well-structured with sections for Returns, Columns, Sorting Options, and Notes. It's a bit long but every section adds useful information. The main purpose is front-loaded in the first sentence.

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?

The description is fairly comprehensive given the tool's complexity, covering purpose, behavior, return columns, sorting, and notes. It is let down by the sorting-field discrepancy and missing parameter explanations, but overall it provides enough context for an agent to invoke the tool correctly in most cases.

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

Parameters2/5

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

The description mentions buy_or_sell meaning and sorting, but it incorrectly says sorting is by 'bought_volume_usd' or 'sold_volume_usd' while the schema's orderBy enum actually uses 'token_trade_volume', 'bought_token_volume', and 'sold_token_volume'. It also does not explain key parameters like page, time_range, include_labels, or min_trade_volume_usd, with schema coverage at 0%.

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?

The description clearly states 'Get TOTAL amount of tokens bought/sold by address for a token on DEX', specifying the verb, resource, and scope. It distinguishes from siblings like token_dex_trades (individual trades) and token_current_top_holders (holders) by focusing on aggregated address-level activity on DEX only.

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?

The description explicitly says 'Use this tool to find out WHO is buying or selling a token (on DEX) AND then you can check if they are liquidating profits or accumulating more.' This provides clear context for when to use it, though it does not explicitly mention alternatives or exclusions beyond the DEX-only scope.

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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