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make_query_public

Change a private Dune Analytics query to public for broader access and collaboration. Provide the query ID to update its visibility settings.

Instructions

Make a private query public, allowing broader access.

Args: query_id: The unique identifier of the query.

Returns: Privacy change confirmation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
query_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions the action ('make public') and outcome ('allowing broader access'), but lacks details on permissions needed, whether the change is reversible, rate limits, or error conditions. This is inadequate for a mutation tool with zero annotation coverage.

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 the core purpose in the first sentence, followed by structured 'Args' and 'Returns' sections. It's efficient with minimal waste, though the 'Returns' section could be integrated more seamlessly.

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 tool's complexity (mutation with privacy implications), lack of annotations, and presence of an output schema (which covers return values), the description is partially complete. It explains the action and parameter but misses behavioral details like authorization needs or side effects, leaving gaps for safe agent use.

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

Parameters4/5

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

The description adds meaningful context for the single parameter 'query_id' by explaining it's 'The unique identifier of the query,' which clarifies its purpose beyond the schema's type 'integer.' With 0% schema description coverage and only one parameter, this compensates well, though it doesn't specify format constraints (e.g., valid range).

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 the specific action ('Make a private query public') and the resource affected ('query'), distinguishing it from siblings like 'make_query_private' (opposite action) and 'update_query' (general modification). The verb 'make' and scope 'allowing broader access' provide precise intent.

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 implies usage context by specifying 'private query' as the target, suggesting this tool is for changing privacy settings. However, it does not explicitly state when to use this versus alternatives like 'update_query' for other modifications or prerequisites (e.g., ownership requirements).

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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