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kenningai

Kenning PG MCP

by kenningai

list_extensions

Returns the purpose of the tool: The generated meta description for the list_extensions tool.

Instructions

List installed and available PostgreSQL extensions with versions and descriptions. Cheap. Check here whether an extension (pg_stat_statements, postgis, hypopg, ...) exists before writing queries that depend on it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations provided, so the description carries the disclosure burden. It signals the tool is 'Cheap' (low cost), disclosing performance characteristics. The read-only nature is implicit from 'list installed and available extensions.' It doesn't describe the output format, but with an output schema present and a 0-param read operation, the behavioral disclosure is adequate.

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?

Three sentences, zero waste. The first sentence states purpose and contents, the second notes cost, the third gives a concrete usage scenario. Every sentence earns its place and the actionable guidance is front-loaded and clear.

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

Completeness5/5

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

For a 0-parameter introspection tool with an output schema present, the description is complete. It explains what data is returned (versions, descriptions), notes cost, and gives a practical use case. No missing prerequisites, parameters, or behavioral caveats are relevant here.

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 tool has 0 parameters, so there is nothing to document. Schema coverage is 100% (trivially). The baseline for 0-param tools is 4, and the description doesn't need to add parameter semantics since none exist. The examples enumerate extensions it will surface, adding semantic color beyond the empty schema.

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?

Specific verb+resource (list extensions) with clear scope: 'installed and available PostgreSQL extensions with versions and descriptions.' The examples (pg_stat_statements, postgis, hypopg) and the phrase 'Cheap' add useful distinctiveness. It's clearly differentiated from sibling list_schemas/list_objects.

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

Usage Guidelines5/5

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

Explicit guidance on when to use: 'Check here whether an extension exists before writing queries that depend on it.' This is a clear usage directive with a concrete scenario. Though it doesn't name alternatives, the purpose (introspection-check before query) is unambiguous for a 0-param read tool.

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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