search_tables

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

With no annotations, the description carries the burden of behavioral disclosure. It reveals that results are paginated to prevent token overflow, which is useful. However, it does not explicitly state that the operation is read-only, what the returned result structure looks like, or how matches are ordered.

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?

The description is three concise sentences: purpose, usage context, and pagination rationale. Every sentence adds useful information, and the content is front-loaded with the core capability. There is no wasted wording.

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?

The schema covers all parameter semantics, and the description adds the key behavioral concern of pagination and token overflow. It is adequate for an agent to call the tool correctly, though a note about the return format would make it complete given there is no output schema.

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 100%, so the parameters pattern, page, type, limit, and compact are all already documented. The description adds general context about name patterns and pagination, but no additional parameter-level detail beyond what the schema provides.

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 a specific verb ('Search') and resource ('tables or columns'), then qualifies it with a clear scope ('by name pattern'). This accurately captures the tool's capability and distinguishes it from sibling tools like get_tables or describe_table, which are not pattern-search operations.

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?

The phrase 'Useful for finding specific tables or columns when you don't know the exact name' gives a clear usage context and implies this tool is the right choice for fuzzy/pattern-based lookup. It does not explicitly contrast with get_tables or raw_query, but the guidance is not misleading and is sufficient for an agent.

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