search_text

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

There are no annotations, so the description carries the full burden. It discloses BM25 score ordering, explains that returned rows are evidence of which documents matched, and describes the live-store behavior. It does not state read-only/auth/rate details, but the search semantics are sufficiently transparent.

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?

Three compact sentences: the first states the core purpose, and the next two add ordering and live-store behavior. Every sentence earns its place with no redundancy.

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 three-parameter search tool with an output schema, the description covers target selection, live-store semantics, and result ordering. Minor omissions such as pagination or result limits do not prevent correct invocation.

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%, and the description compensates well by defining target values and the meaning of live. query is only implied by '全文検索', but it is the required parameter and its purpose is obvious from the tool name and context.

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?

The description opens with 'FTS 全文検索' (full-text search) and specifies the two target corpora: 'papers' (abstract) and 'comments' (text). This clearly separates search_text from sibling tools like run_sql and get_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?

It explicitly states when to use live=True (after refresh_data, on the live store) and which target to choose. It does not explicitly say when not to use the tool or compare it to run_sql, but the usage context is otherwise clear.

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