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delete_table

Permanently delete a table and all its data from the Dune Analytics database. This irreversible action removes specified blockchain data tables to manage storage and clean datasets.

Instructions

Permanently delete a table and all its data.

WARNING: This operation is irreversible!

Args: namespace: Namespace of the table. table_name: Name of the table to delete.

Returns: Deletion confirmation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
namespaceYes
table_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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 effectively communicates the destructive nature ('permanently delete', 'irreversible'), which is critical for a mutation tool. However, it lacks details on permissions, rate limits, or error conditions (e.g., what happens if the table doesn't exist), leaving some behavioral aspects uncovered.

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?

The description is front-loaded with the core action and warning, followed by structured Arg/Return sections. Every sentence earns its place: the first states the purpose, the second warns, and the bullet points clarify parameters and output without redundancy. It is appropriately sized for a destructive operation.

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?

Given the tool's high complexity (destructive mutation), no annotations, and an output schema (implied by 'Returns'), the description does well by emphasizing irreversibility and confirming deletion. However, it could be more complete by addressing prerequisites (e.g., required permissions) or error handling, which are important for such a critical tool.

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?

Schema description coverage is 0%, so the description must compensate. It adds meaningful context by explaining that 'namespace' and 'table_name' identify the table to delete, which clarifies their roles beyond the bare schema. However, it does not provide format examples or constraints (e.g., naming rules), leaving some semantic gaps.

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 ('permanently delete') and resource ('a table and all its data'), distinguishing it from siblings like 'clear_table' (which likely removes data but not the table structure) or 'archive_query' (which deals with queries rather than tables). The verb+resource combination is precise and unambiguous.

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 clear context with the 'WARNING: This operation is irreversible!' statement, implying it should be used cautiously and not for reversible operations. However, it does not explicitly name alternatives (e.g., 'clear_table' for removing data without deleting the table) or specify when-not-to-use scenarios beyond the warning, which prevents a perfect score.

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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