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table_stats

Retrieve PostgreSQL table statistics including row count, size metrics, and vacuum information to monitor database performance and storage usage.

Instructions

Get statistics for a table (row count, size, bloat).

Args:
    table_name: Name of the table
    schema: Schema name (default: public)
    
Returns:
    Table statistics including row count, sizes, and vacuum info

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
table_nameYes
schemaNopublic
Behavior3/5

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

With no annotations provided, the description carries the full burden. It clearly describes the read-only nature ('Get statistics') and specifies what information is returned, but lacks details on behavioral aspects like error handling, performance implications, or whether it requires specific permissions.

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 well-structured and appropriately sized. It front-loads the core purpose, then clearly lists arguments and returns in separate sections. Every sentence adds value with no redundant information.

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 moderate complexity (2 parameters, no output schema, no annotations), the description is adequate but has gaps. It covers the purpose and parameters well, but lacks information about return format details (e.g., structure of 'vacuum info') and doesn't address potential limitations or error cases.

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 significant value beyond the input schema, which has 0% description coverage. It explains both parameters: 'table_name' as 'Name of the table' and 'schema' as 'Schema name (default: public)', including the default value. This compensates well 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.

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 with a specific verb ('Get') and resource ('statistics for a table'), and lists the specific statistics returned (row count, size, bloat). However, it doesn't explicitly differentiate from sibling tools like 'describe_table' or 'list_tables', which might also provide table information.

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. It doesn't mention sibling tools like 'describe_table' (which might provide metadata) or 'list_tables' (which might list tables without statistics), leaving the agent to infer usage context.

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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