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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: it queries Dune Analytics with a specific query ID, returns a tabulated string format, handles failures by returning an empty string, and can raise exceptions on errors. This covers key operational aspects without contradictions.

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

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

The description is efficiently structured with a clear purpose statement followed by specific implementation details, parameter documentation, return value explanation, and error handling. Every sentence adds value without redundancy, and information is appropriately front-loaded.

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

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

For a single-parameter tool with no annotations and no output schema, the description provides comprehensive context: purpose, data source, query specifics, return format, failure behavior, and error handling. The only minor gap is that it doesn't explicitly mention the tool is read-only (though this is implied by 'retrieve'), but overall it's highly complete.

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

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

The schema description coverage is 0%, so the description must fully compensate. It provides excellent parameter semantics: clearly explains the 'limit' parameter's purpose, optional nature, default value, and effect. This adds substantial meaning beyond what the bare schema provides.

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

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

The description clearly states the specific action ('retrieve'), target resources ('top profitable wallets on Pumpfun and Pumpswap'), and timeframe ('last 30 days'). It distinguishes this from sibling tools like 'get_total_wallets' or 'get_trading_wallets' by focusing on profitability ranking rather than counts or distribution.

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

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

The description provides clear context about when to use this tool (to get ranked profitable wallets over 30 days), but doesn't explicitly state when NOT to use it or name specific alternatives among the sibling tools. The context is well-defined but lacks explicit exclusions or comparative guidance.

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

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

With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: it describes the data source (Dune Analytics query), failure behavior (returns 0 if query fails), and error handling (raises Exception on API/data retrieval errors). It doesn't mention rate limits, caching, or authentication needs, but covers core operational aspects adequately.

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

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

The description is perfectly structured and concise: first sentence states purpose, second explains implementation, followed by clear 'Returns' and 'Raises' sections. Every sentence adds value with zero waste, and information is front-loaded appropriately for a zero-parameter tool.

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

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

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is nearly complete: it explains what it does, how it works, what it returns, and error behavior. The only minor gap is lack of sibling differentiation, but for a straightforward query tool, this provides sufficient context for an agent to use it correctly.

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

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

The tool has 0 parameters with 100% schema description coverage, so the baseline is 4. The description correctly indicates no parameters are needed ('This function queries...'), adding no unnecessary parameter information while matching the schema's empty state.

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

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

The description clearly states the specific action ('Retrieve'), resource ('total number of wallets'), and scope ('on Pumpfun and Pumpswap platforms'), distinguishing it from sibling tools like get_alpha_wallets or get_trading_wallets which focus on different wallet subsets. It provides a complete purpose statement without being vague or tautological.

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

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

The description provides no guidance on when to use this tool versus its siblings (get_alpha_wallets, get_trading_wallet_distribution, get_trading_wallets). It mentions the data source (Dune Analytics query ID: 5239155) but doesn't specify use cases, prerequisites, or alternatives, leaving the agent with no contextual decision-making help.

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

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

With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: data source (Dune Analytics), query failure behavior (returns empty string), error handling (raises Exception), and output format (tabulated string). It doesn't mention rate limits or authentication needs, but covers most essential operational aspects.

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

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

The description is well-structured with clear sections (purpose, data source, returns, raises) and efficiently conveys necessary information in 5 sentences. It could be slightly more concise by combining some sentences, but overall wastes no space.

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

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

For a parameterless tool with no annotations and no output schema, the description provides comprehensive context: purpose, data source, exclusion criteria, return format, and error behavior. The only minor gap is not explicitly stating the volume tier ranges, but given the query ID reference, this is reasonable.

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

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

With 0 parameters and 100% schema coverage, the baseline is 4. The description appropriately explains this is a parameterless function that retrieves pre-defined data, which aligns perfectly with the empty input schema.

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

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

The description clearly states the specific action ('Retrieve the distribution of wallets'), resource ('wallets by trading volume on Pumpfun and Pumpswap'), and scope ('excluding bots'). It distinguishes from sibling tools like 'get_total_wallets' by specifying trading volume distribution rather than total counts.

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

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

The description implies usage context through 'excluding bots' and mentions data source (Dune Analytics query ID: 5239138), but doesn't explicitly state when to use this tool versus alternatives like 'get_trading_wallets' or provide clear exclusions. The guidance is contextual but not explicit about alternatives.

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

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

With no annotations provided, the description carries the full burden and does well by disclosing key behaviors: it queries Dune Analytics (query ID specified), returns a tabulated string, handles failures with an empty string, and raises exceptions on errors. It covers data source, output format, and error handling, though it could mention rate limits or permissions.

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

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

The description is well-structured and front-loaded with the core purpose, followed by details on args, returns, and raises. Every sentence adds value without redundancy, making it efficient and easy to parse.

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

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

Given the tool's moderate complexity (1 parameter, no output schema, no annotations), the description is largely complete: it explains purpose, parameters, return format, and error behavior. It could be slightly enhanced by mentioning data freshness or query limitations, but it covers essential aspects adequately.

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

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

The description adds significant meaning beyond the input schema, which has 0% coverage. It explains the 'limit' parameter's purpose (maximum number of wallets), default value (10), and effect on the output, compensating fully for the schema's lack of descriptions.

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

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

The description clearly states the specific action ('Retrieve'), resource ('top wallets by all-time trading volume'), and scope ('on Pumpfun and Pumpswap'), distinguishing it from sibling tools like get_alpha_wallets or get_total_wallets by focusing on trading volume ranking.

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

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

The description implies usage for fetching ranked trading volume data but does not explicitly state when to use this tool versus alternatives like get_trading_wallet_distribution or other siblings. It provides context (ranking by volume) but lacks explicit guidance on exclusions or comparisons.

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