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execute_query

Run saved blockchain data queries on Dune Analytics by ID to analyze on-chain activity across Ethereum, Solana, and other networks. Pass parameters and select performance tier for custom execution.

Instructions

Execute a saved query by its ID.

Args: query_id: The unique identifier of the saved query. query_parameters: Optional parameters to pass to the query (key-value pairs). performance: Performance tier - "medium" (default) or "large".

Returns: Execution details including execution_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
query_idYes
query_parametersNo
performanceNomedium

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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 mentions the action ('Execute') and return value ('Execution details including execution_id'), but lacks critical information about side effects (e.g., does execution consume resources?), permissions required, rate limits, or what happens if the query fails. This is inadequate for a tool that likely performs server-side operations.

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 clear sections (Args, Returns) and uses minimal sentences. However, the 'Args' section could be more integrated into the flow rather than listed separately, and some details feel slightly redundant (e.g., repeating 'query' in parameter names).

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

Completeness3/5

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

Given the complexity (3 parameters, no annotations, but has output schema), the description is moderately complete. It covers the basic purpose and parameters, and the output schema handles return values. However, it misses important context like error handling, execution timeouts, or how this interacts with sibling tools (e.g., 'get_execution_status'), leaving gaps for an agent to use it effectively.

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

Parameters3/5

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

The description lists all three parameters with brief explanations, which adds value since schema description coverage is 0%. However, it doesn't explain the format of 'query_parameters' (e.g., expected key-value structure) or practical implications of 'performance' tiers (e.g., cost or speed differences). The coverage is basic but compensates somewhat for the schema gap.

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

Purpose4/5

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

The description clearly states the action ('Execute a saved query') and the resource ('by its ID'), making the purpose immediately understandable. However, it doesn't explicitly distinguish this tool from sibling tools like 'execute_sql' or 'get_query_results', which could cause confusion about when to use each.

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

Usage Guidelines2/5

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 alternatives like 'execute_sql' (for direct SQL execution) or 'get_query_results' (for retrieving results). It also doesn't mention prerequisites such as needing a saved query ID or when performance tiers matter.

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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