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Apply DB Fix

nexusai_db_apply_fix
Destructive

Apply a DDL fix previously returned by nexusai_db_propose_fix. Show the proposal to the person and get their explicit approval before calling this tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dbSourceIdYesDB source UUID.
proposalIdYesFix proposal UUID.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true, readOnlyHint=false, and openWorldHint=true, so the safety profile is covered. The description adds context beyond that: the change is DDL (schema-mutating, not data-only), and there is a mandatory human-approval gate before invocation. It stops short of stating irreversibility or rollback 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?

Two sentences, zero filler, front-loaded with the action and its origin tool. The approval requirement follows immediately as a hard precondition.

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 destructive, no-output-schema mutation tool whose annotations already cover the safety flags, the description supplies the essential workflow context (provenance plus approval gate). It omits failure behavior and reversibility, which are the only notable remaining gaps.

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

Parameters4/5

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

Schema coverage is 100% and both parameters carry clear descriptions, so the baseline is 3. The description adds provenance the schema lacks: proposalId is specifically the identifier of a proposal previously emitted by nexusai_db_propose_fix, which tells the agent where the value must come from rather than just its type.

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?

States a specific verb and resource ('Apply a DDL fix') and explicitly ties the tool to the sibling that produces its input, 'nexusai_db_propose_fix'. An agent can distinguish this from nexusai_db_propose_fix and the other db_* siblings without opening either schema.

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

Usage Guidelines5/5

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

Gives the explicit precondition for calling: the proposal must come from nexusai_db_propose_fix, and the human must be shown the proposal and give explicit approval first. This is a genuine when-to-use gate that routes the agent through the correct workflow rather than leaving sequencing to inference.

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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