Nansen

by io.github.hurcanNansen

Finding prediction market top holders

prediction_market_top_holders

Largest current holders for a Polymarket market.

Key fields:

Positions are share balances, not USD notional.
Position Value USD is current marked value, not payout at resolution.
Side Held is the share side currently held.

Pitfalls:

The visible holder table is the source of truth for holder-side concentration — do not infer risk, max loss, or potential profit unless the tool output explicitly provides it.
Output summary is based only on shown rows, not the entire holder table.
Large visible positions or labels do not by themselves identify smart money unless Nansen smart-money-labelled data supports it.

Prerequisites: If marketId is unknown, call prediction_market_lookup first.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`request`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4/5.0

Behavior4/5

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

No annotations are present, so the description carries the full burden of transparency. It explicitly explains that positions are share balances, 'Position Value USD' is marked value not resolution payout, and that output is based on shown rows only. It also warns against inferring risk or smart money without explicit support. However, it does not mention pagination behavior or rate limits.

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 front-loaded with a one-sentence summary, then uses concise bullet lists for key fields and pitfalls. It is longer than average, but each bullet adds meaningful interpretive guidance with no filler.

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?

An output schema exists, so return-value details are not required in the description. The description covers important interpretation pitfalls and prerequisites, but it does not clarify pagination behavior or the scope of rows returned despite the page parameter, leaving a minor completeness gap.

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?

Schema description coverage is 0%, and the description only references marketId in the prerequisite. It does not explain the request wrapper, page, orderBy, or orderByDirection semantics, leaving a significant gap that the description does not compensate for.

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 opens with 'Largest current holders for a Polymarket market,' which is a specific verb+resource pair that clearly states the tool's function. It also distinguishes this from sibling tools like prediction_market_position_detail or prediction_market_pnl_leaderboard by focusing on holder lists.

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 provides a clear context: use this to see the largest current holders of a specific Polymarket market. It gives a prerequisite ('If marketId is unknown, call prediction_market_lookup first'), though it does not explicitly contrast with alternatives or state when not to use the tool.

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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