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db_detect_drift

Audit database annotations against live schema. Identify orphaned annotations and undocumented tables to maintain schema coverage.

Instructions

Audit saved annotations against the live database schema (read-only).

Surfaces drift after the schema evolves:
  - orphaned annotations — a table or column you annotated that no longer
    exists in the DB. Remove with db_forget, or db_deprecate if pending.
  - undocumented tables — live tables with no annotation yet (coverage gaps).

Changes nothing — purely a report. Run after schema changes, or periodically.

Args:
    connection: Connection name. Defaults to first defined.

Returns:
    {connection, orphaned_tables, orphaned_columns, undocumented_tables,
     undocumented_truncated, summary}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
connectionNo
Behavior5/5

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

The description explicitly states the tool is read-only ('Changes nothing — purely a report.') and details what it surfaces (orphaned annotations, undocumented tables). It also outlines the return structure (connection, orphaned_tables, etc.), providing full transparency without relying on annotations.

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 concise and well-structured: it opens with a clear verb-resource statement, uses bullet points for key outputs, and includes a separate Args/Returns section. Every sentence adds value without redundancy.

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

Completeness5/5

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

Despite having only one optional parameter and no output schema, the description fully covers the tool's function, when to use it, what it detects, and the format of its return. No gaps remain for the intended use case.

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?

The input schema only has one parameter (connection) with default null. The description adds meaning by stating 'Defaults to first defined,' which goes beyond the schema's default value. Given the parameter's simplicity, the description provides sufficient context.

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 tool's purpose: 'Audit saved annotations against the live database schema (read-only).' It specifies the verb (audit) and the resource (annotations vs live schema), and distinguishes itself from sibling tools like db_forget and db_deprecate by emphasizing it is a read-only report that detects drift.

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?

The description provides explicit when-to-use guidance: 'Run after schema changes, or periodically.' It also advises on follow-up actions ('Remove with db_forget, or db_deprecate if pending.'), making the usage context clear.

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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