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db_deprecate

Flag a table or column as deprecated to prevent AI reliance, without deleting it. Reversible action keeps schema intact.

Instructions

Soft-retire a table or column annotation — flag it stale without deleting it.

Use when a table/column still exists but should no longer be relied on. The
deprecation flag is surfaced in db_get_schema so the AI is warned off it on
future calls. Reversible via undo=True. To remove an annotation entirely
(e.g. the column was dropped from the DB), use db_forget instead.

Args:
    table:      Table name, optionally schema-qualified (e.g. "users",
                "public.users", "dbo.Orders", "mydb.orders").
    connection: Connection name. Defaults to first defined.
    column:     Column to deprecate. Omit to deprecate the whole table.
    reason:     Why it's deprecated (e.g. "replaced by status_v2").
    undo:       Clear the deprecation flag instead of setting it.

Returns:
    {table, connection, column, target, deprecated, reason}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableYes
connectionNo
columnNo
reasonNo
undoNo
Behavior4/5

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

No annotations provided, but description explains the deprecation flag is surfaced in db_get_schema and that operation is reversible. Lacks details on permissions or side effects, but sufficient for a soft-retire tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with summary, usage guidelines, and argument list. Slightly wordy but each sentence adds value. No 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?

Given 5 parameters, no output schema, and no annotations, the description covers all inputs, explains return format, and mentions interaction with db_get_schema. Distinguishes from sibling db_forget.

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

Parameters5/5

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

Schema coverage is 0%, but description provides full argument list with detailed explanations, defaults, and usage nuances (e.g., connection defaults to first defined, column omitted means whole table).

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?

Description clearly states the tool soft-retires a table or column annotation, distinguishing it from db_forget which removes entirely. Specific verb+resource combination.

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?

Explicitly states when to use (table/column still exists, should not be relied on) and when not (use db_forget instead). Also mentions reversibility via undo=True.

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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