get_table_sampleReturns a sample of rows from a specified MySQL table to inspect its data. Use optional limit and database parameters to control the query.
Get sample rows from a table
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of rows to return (1-50, default 5) | |
| table | Yes | Table name | |
| database | No | Optional database to read from for this call only, without changing the active connection |
Changes observed during successful MCP inspections.
v1.1.5Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the operation read-only, idempotent, and non-destructive, so no safety contradiction exists. The description adds only the word 'sample', which hints at subset behavior, but does not explain whether rows are random, ordered, or arbitrary.
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?
The description is a single focused sentence with no filler. It is appropriately front-loaded and easy for an agent to parse quickly.
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 itself is simple and the annotations cover safety, but no output schema exists and the description does not clarify the nature of the sample or distinguish it from running a query. An agent could invoke it correctly, yet the ambiguity about ordering and randomness remains a gap.
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 description coverage is 100%, so the parameters are already well documented in the input schema. The description adds no additional parameter-level meaning beyond what the schema provides.
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?
The description uses a specific verb ('Get') and identifies the resource ('sample rows from a table'), making the core function clear. It does not explicitly distinguish this from siblings like describe_table or run_query, but the phrase 'sample rows' communicates the idea of a lightweight preview.
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 guidance is given about when to prefer this tool over alternatives such as run_query or describe_table. The description implies quick data preview but never states the intended context or mentions exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.