search_messages

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions implementation details (FTS5/LIKE fallback) and default values (limit default 50), but doesn't cover important aspects like rate limits, authentication requirements, pagination behavior, error conditions, or what the return format looks like. For a search tool with 7 parameters and no output schema, this leaves significant gaps.

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 well-structured with a clear purpose statement followed by parameter explanations in a consistent format. Every sentence earns its place, though the parameter explanations could be slightly more concise. The information is front-loaded with the core functionality stated first.

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 tool's complexity (7 parameters, search functionality), lack of annotations, and no output schema, the description is incomplete. While it excellently documents parameters, it misses crucial behavioral context like return format, error handling, performance characteristics, and how results are structured. For a search tool without output schema, describing the return format would be particularly important.

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?

With 0% schema description coverage, the description fully compensates by providing clear explanations for all 7 parameters. Each parameter gets a concise explanation that adds meaning beyond the schema's titles, including optionality indicators, format requirements (YYYY-MM-DD or RFC3339 for dates), enumerated values (image|video|audio|document for media_type), and default values (limit default 50).

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 the tool performs 'Full-text search across WhatsApp messages' with specific implementation details (FTS5 if available, LIKE fallback). It distinguishes itself from sibling tools like 'list_messages' by focusing on search functionality rather than listing, and from 'search_contacts' by targeting messages instead of contacts.

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 description implies usage context through parameter explanations (e.g., 'Optional chat JID filter'), but doesn't explicitly state when to use this tool versus alternatives like 'list_messages' or 'show_message'. It provides some guidance through parameter semantics but lacks explicit comparison with sibling tools.

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