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

Annotations already indicate read-only and idempotent behavior. The description adds valuable behavioral context by explaining that it does an AND search (all words must match) and is case-insensitive, which goes beyond the standard annotations. It also clarifies that it searches across all documentation files, providing scope.

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 two sentences long and efficiently conveys the core function, matching behavior, and usage context. It is front-loaded with the main purpose and does not waste words on redundant information. Every sentence contributes to understanding the tool.

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 simplicity, the presence of a thorough input schema, output schema, and clear annotations, the description is complete. It explains the search scope, matching rule, and provides a usage scenario. It does not need to explain return values because the output schema covers that.

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 baseline is 3. The description does not directly elaborate on parameters, but the schema already provides thorough descriptions for query, max_results, and context_chars. The tool description's mention of 'every word' reinforces the query parameter semantics, but it doesn't add significant new meaning beyond the schema.

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's function: 'Full-text search across all Gonka documentation files.' It also specifies the matching semantics (AND search, case-insensitive) and distinguishes it from query_graph by noting that it should be used when query_graph() returns no results, which effectively differentiates it from a key sibling.

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 explicitly tells when to use this tool: 'Use this when query_graph() returns no results.' This provides direct guidance versus a specific alternative. Additionally, the query parameter description advises preferring fewer, more specific words, which is useful usage guidance.

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