Skip to main content
Glama

Checking Smart Money positions

smart_traders_and_funds_token_balances

Get aggregated (not per wallet) smart trader and fund (EXCLUDES whales, large holders, influencers, etc.) token balances and 24h change per chain for all chains (default is ['all'], which queries all supported chains) or specific chain(s). Use filters to narrow down the results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.1/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses aggregation, exclusion of certain smart money categories, per-chain support with default 'all', and the existence of filters. This provides meaningful behavior beyond the name, though it does not mention pagination or response details (output schema covers return structure).

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

Conciseness5/5

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

Two sentences, front-loaded with the core function and key constraints. The first sentence packs substantial detail (aggregation, exclusions, chains, 24h change) without fluff; the second gives a practical tip. Every word earns its place.

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 provides the essential gist, defaults, and scope for an agent to select the tool correctly. Given the complex nested request object and the presence of an output schema, it covers the core usage, though it could briefly mention pagination or the stablecoin/native token toggles. Still, it is sufficient for initial understanding.

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 generically references 'filters' and 'per chain' without detailing parameters like orderBy, minHolders, includeStablecoin, or includeSmartMoneyLabels. The input schema itself has detailed parameter descriptions, but the tool description adds minimal value beyond that.

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 states 'Get aggregated (not per wallet) smart trader and fund token balances and 24h change per chain' – a specific verb and resource, and explicitly excludes whales, large holders, and influencers. This clearly distinguishes it from sibling tools like smart_traders_and_funds_perp_trades and address_historical_balances.

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 gives clear context: it returns aggregated balances for selected chains, defaults to all supported chains, and advises 'Use filters to narrow down the results.' It does not explicitly name alternatives or when-not-to-use, but the exclusions and aggregation scope make the appropriate use case obvious.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

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.

Resources