Retrieve a PostgreSQL table's columns, data types, and primary keys by schema and table name to inspect its structure before querying or modifying it.
Detail the columns, types, and primary keys of a specific table (FR-002)
| Name | Required | Description | Default |
|---|---|---|---|
| table | Yes | Table name | |
| schema | Yes | Schema name (e.g. 'public') |
Changes observed during successful MCP inspections.
v0.1.4Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the safe-read profile is covered. The description adds value by naming the return content (columns, types, primary keys), but does not discuss permissions, error behavior, or limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with no filler. The trailing '(FR-002)' reference is not useful to an agent and slightly detracts from otherwise tight phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, parameters are fully documented, and annotations cover safety. Since there is no output schema, the description usefully states what is returned (columns, types, primary keys); the main remaining gap is lack of explicit usage guidance versus sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents both parameters. The description adds no syntax or constraints beyond what the schema provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ("Detail") and resource ("a specific table"), listing the returned elements: columns, types, and primary keys. This distinguishes it contextually from list_tables, but it does not explicitly name the sibling tool it differs from.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for inspecting a single table's structure, but gives no explicit when-to-use guidance, prerequisites, or comparison to alternatives like list_tables or run_query.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.