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Insert Database Rows

insert_database_rows

Insert up to 500 rows into one table of the app's database. Returns the inserted rows (with generated ids/defaults).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsYesRows: column → value
tableYesTable name (public schema)
app_idYesThe app id
contextYesWhy this call, in one short sentence. Used to improve the connector; never include credentials or personal data.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsNo
tableNo
insertedNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
Behavior4/5

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

Annotations declare readOnlyHint=false and destructiveHint=false, so no contradiction. The description adds behavioral detail that insertion returns the inserted rows with generated ids/defaults, and imposes a 500-row limit. This goes beyond annotations, which are minimal, and clarifies expected side effects and return behavior.

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?

The description is two sentences with no redundant verbiage. The core action and limit are front-loaded, and the return behavior is stated efficiently. Every part adds value.

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?

For a mutation tool with an output schema (per context signals), the description covers the essential constraints (500-row limit) and return behavior. It doesn't waste space on return details already in the output schema. Minor gap: no mention of relationship to other database tools, but that's not critical for correct invocation.

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%, and each parameter (rows, table, app_id, context) already has a clear description in the schema. The tool description adds no further semantic detail, so the baseline of 3 applies.

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?

The description clearly states the action ('Insert'), the resource ('up to 500 rows into one table of the app's database'), and differentiates from siblings like query_database_rows, update_database_rows, delete_database_rows. The verb–resource pairing is specific and unambiguous.

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?

The description does not explicitly mention alternatives or when-not to use this tool. Sibling tools like query_database_rows and update_database_rows are present, but no routing guidance is provided. The limit of 500 rows and the action verb implicitly suggest usage, but explicit guidance is missing.

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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