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by ai.peakflo
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table_insert

Insert a single row into a data table.

Provide the data as a JSON object where keys are column names and values are the row values. Returns the inserted row with all columns (including auto-generated ones like id, created_at).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "tableId": "<tableId>",
      "data": "<data>"
    },
    "name": "table_insert"
  }
}

Input Schema

NameRequiredDescriptionDefault
dataYesJSON object of column-value pairs to insert, e.g. {"name": "Acme", "amount": 100}
tableIdYesThe data table ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint false, destructiveHint false), and the description adds genuinely new behavior: it returns the inserted row including auto-generated columns like id and created_at. It omits failure behavior for type mismatches or unknown columns, which keeps it from a 5.

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 short sentences, front-loaded with the action, then the input contract, then the return shape. Nothing is redundant or padded.

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

Completeness4/5

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

With only two parameters, full schema coverage, and no output schema, the description supplies the key missing piece: what the call returns. It does not cover error conditions or schema-validation guidance, a minor gap for a simple insert tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the required/optional structure, the tableId meaning, and the JSON column-value format are already documented in the schema. The description's restatement that keys are column names adds no syntax or type detail beyond what the schema provides, so baseline 3 applies.

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?

A specific verb and resource are stated: 'Insert a single row into a data table.' The phrase 'single row' implicitly distinguishes it from table_bulk_insert, though no sibling is named explicitly.

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

Usage Guidelines3/5

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

Usage is only implied: 'single row' hints that bulk loads should use another tool, but the description never states when to use this versus table_bulk_insert or table_update, nor any prerequisites such as verifying columns via table_schema first.

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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