search_tables

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

With no annotations, description fully bears behavioural disclosure. It explains it returns ranked TableSummary with curation, includes examples of output, and schema description adds case-insensitivity. No destructive behavior or auth needs mentioned, which is appropriate for a read-only search.

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?

Description is well-organized with sections, bullet points, and code examples. Every sentence earns its place—no fluff. Front-loaded with purpose, then usage guidance, then examples, then return info. Efficient yet comprehensive.

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?

Given the output schema exists and the description already explains return type (List of TableSummary with fields), ranking, and curation, the description is complete. No prerequisites or side effects needed; all relevant information for a search tool is present.

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 already provides descriptions and examples for both parameters (100% coverage). Description adds usage context through example calls and explanation of results, but doesn't significantly extend parameter semantics beyond schema. The example block is helpful, so slight upgrade from baseline 3.

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 clearly states it performs fuzzy-search over RBA F-tables by name and topic. It distinguishes from siblings like describe_table and get_data by focusing on discovery when the exact ID is unknown. Examples and mention of curated tables reinforce specificity.

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?

Explicitly states 'Use this when you don't know the exact table ID.' Provides three bullet points for when to use: natural-language queries, topic discovery, and catalog enumeration. Does not explicitly mention when not to use or alternatives, but context with siblings implies alternatives.

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