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drop_table

Delete existing tables from CockroachDB with confirmations to ensure secure schema management and test environment cleanup. Specify the table name for precise execution.

Instructions

Facilitate the deletion of existing tables from the database. This tool is useful for cleaning up test environments or managing schema changes, always with the necessary confirmations for security.

Args: table_name (str): Name of the table to drop.

Returns: A success message or an error message.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
table_nameYes
Behavior3/5

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 that the tool 'always with the necessary confirmations for security,' indicating a safety mechanism, and mentions it's for deletion, implying destructive behavior. However, it lacks details on permissions required, whether deletions are reversible, rate limits, or error handling specifics, leaving gaps for a mutation tool.

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 appropriately sized with three sentences: purpose, usage context, and parameter/return info. It is front-loaded with the core action. The Args and Returns sections are structured but slightly verbose; every sentence adds value, though 'always with the necessary confirmations' could be more concise.

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 (destructive mutation), no annotations, no output schema, and low schema coverage, the description is moderately complete. It covers purpose, usage context, and parameter semantics but lacks details on behavioral aspects like error messages, confirmation processes, or integration with other tools. For a high-risk operation, more context would be beneficial.

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 input schema has 1 parameter with 0% description coverage, so the description must compensate. It adds meaning by specifying 'table_name (str): Name of the table to drop,' which clarifies the parameter's purpose beyond the schema's basic type. Since there are no other parameters, this is sufficient, but it doesn't detail constraints like table existence or naming rules.

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 tool's purpose as 'deletion of existing tables from the database' with a specific verb (deletion/facilitate deletion) and resource (tables). It distinguishes from siblings like drop_database, drop_index, and drop_view by specifying tables. However, it doesn't explicitly contrast with other table-related tools like create_table or describe_table, keeping it from a perfect score.

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

Usage Guidelines3/5

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

The description provides implied usage guidance by mentioning 'useful for cleaning up test environments or managing schema changes,' which suggests contexts for use. However, it does not explicitly state when to use this tool versus alternatives (e.g., drop_database for databases, drop_view for views) or list prerequisites like needing table existence. No explicit exclusions are provided.

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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