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Save a table search revision

configure_table_search

Saves a draft search configuration for one immutable table_version_id. expected_revision is the selected draft id reported by inspect_table_search, or null when none; a stale head is refused. spec omitted uses the sealed recipe's spec. semantic_evaluation contains actual resolved evaluation cases. Returns table_id, table_version_id, search_revision_id and validation evidence. Starts no index build. Next: preview_table_search to check which rows the draft admits, then build_table_search with those exact coordinates. Keep idempotency_key unchanged on reconciliation; do not invent a new revision to escape a failure.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
specNo
table_idYes
idempotency_keyNo
table_version_idYes
expected_revisionYes
semantic_evaluationNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnly=false, destructive=false, idempotent=false, openWorld=false, so the safety profile is covered; the description goes further and discloses optimistic-concurrency behavior ('a stale head is refused'), the side-effect boundary ('Starts no index build'), and the return payload. The idempotency_key retry advice is consistent with, not contrary to, idempotentHint=false.

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?

Front-loaded with purpose, then parameter semantics, return values, effect boundary, and next steps in that order. It is dense and clause-heavy for a single save operation, but each clause carries distinct operational information, so nothing is wasted.

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?

For a 6-parameter mutation with nested objects, no output schema, and 0% schema coverage, the description supplies the missing pieces: concurrency precondition, defaults, side-effect scope, returned identifiers, and the follow-on tool sequence. An agent has everything needed to call it correctly.

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 description coverage is 0%, so the description carries the load, and it does well: expected_revision's source (inspect_table_search draft id) and null semantics, spec's default when omitted, and semantic_evaluation's content. It does not, however, give any structure for the two nested free-form objects (spec, semantic_evaluation) or explain table_id, so a small gap remains.

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+resource+scope: 'Saves a draft search configuration for one immutable table_version_id.' That immediately separates it from sibling write tools (build_table_search, preview_table_search, propose_revision, inspect_table_search) without the agent needing to open any 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?

Explicitly routes the workflow: 'Next: preview_table_search to check which rows the draft admits, then build_table_search with those exact coordinates,' and adds an exclusion-style rule ('do not invent a new revision to escape a failure'). Both the when and the when-not are stated, with named alternatives.

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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