Retrieve a table’s column names, data types, notes, and three sample rows to inspect its structure and contents before writing SQL queries.
Columns, types and notes for one table, plus 3 sample rows.
| Name | Required | Description | Default |
|---|---|---|---|
| table | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, but it does disclose real behavior: the response includes column notes and a fixed 3-row sample, which signals cost/content on large tables. It omits read-only confirmation, behavior for missing tables, and whether sampling is truncated or randomized.
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 zero filler. It is arguably over-terse for a tool that must compensate for an undocumented parameter, but nothing is wasted.
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?
For a simple one-parameter read tool with no output schema, disclosing the returned fields and the 3-row sample meaningfully substitutes for the missing output schema. The identifier format and error/edge-case behavior remain unaddressed.
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 0%, so the description must define the single 'table' parameter, and it only says 'one table'. It does not clarify whether this is a bare name, a schema-qualified name, or an identifier.
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?
Names the exact content returned (columns, types, notes) scoped to 'one table', which implicitly separates it from list_tables (many tables) and run_select (arbitrary query). The verb is nominal rather than imperative, but the resource and scope are unambiguous.
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?
No statement of when to prefer this over list_tables or run_select, and no prerequisites. An agent must infer that this is the exploratory step before composing a query.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.