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

Annotations only supply the safety flags (readOnlyHint=false, idempotentHint=false, destructiveHint=false, openWorldHint=false); the description adds substantial context beyond them: the SEARCH_REVISION_CONFLICT refusal on stale bases, refusal on duplicate or >16 case_ids, 'Starts no build,' the fact that the returned revision becomes the selected draft, and idempotency_key guidance for reconciling an uncertain outcome. The idempotency_key advice is a mild tension with idempotentHint=false but is consistent with per-key deduplication and is best read as additional context, not a contradiction.

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

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

Purpose and the base-revision rule are front-loaded, and nearly every clause carries actionable information with little filler. The downside is structure: it is delivered as a dense, semicolon-chained block rather than separated sections, which makes scanning harder than the content warrants.

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

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

For a 5-parameter mutation tool with no output schema and no annotation detail, the description covers preconditions, refusal codes, required input grammar, the return artifact ('Returns the new table-search-revision.v1 with search_revision_id and base_revision_id, which becomes the selected draft'), the absence of a build step, and the follow-up calls. Nothing an agent needs in order to invoke it correctly is missing.

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

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

Schema description coverage is 0%, so the description must carry the semantic load, and it does: it enumerates the case fields (case_id, kind paraphrase|hard_negative, query, top_k, required_locators, forbidden_locators), defines a locator as [part, row] with zero-based part and row, constrains locator provenance (must come from the person or a prior get_search_evaluation ranked_locators, never from sample_table/preview_table_search row positions), requires a hard_negative to name a forbidden row, and explains the base-selection semantics of search_revision_id vs table_version_id.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: it 'declares a new draft revision that carries the base revision's spec and its evaluation cases with cases added,' naming the exact artifact produced (table-search-revision.v1 with search_revision_id and base_revision_id). It also separates itself from the downstream build step by stating 'Starts no build,' so an agent can tell it apart from build_table_search without opening a schema.

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

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

Gives clear operating context: the base revision is selected explicitly via search_revision_id or defaults to the version's selected draft, which must still be the selected draft, and a stale one is refused with SEARCH_REVISION_CONFLICT (re-read inspect_table_search status). It also sequences the workflow ('Next: build_table_search for that revision, then get_search_evaluation'), though it never names a tool that would be the alternative in a given scenario, so it stops short of explicit when-not guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.