get_doc

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

With no annotations, the description carries the full burden. It discloses behavior via content richness (full text, code blocks, metadata), batch limits (up to 10 IDs), and return fields. However, there is a minor inconsistency: 'unlimited size' vs. 'up to 18K+ characters', which could confuse agents about actual limits. Still, it provides substantial behavioral context.

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 clear sections and emoji headers, making it scannable. It is longer than strictly necessary for one parameter, but each section (content richness, usage patterns, what you get, strategy) earns its place by providing actionable guidance. Slight verbosity prevents a perfect score.

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 has one parameter, no output schema, and no annotations, the description covers all necessary bases: return fields (title, url, content, contentLength, codeBlocks), usage patterns, batch limits, and integration with search_docs. It is fully self-contained for an agent to decide when and how to invoke it.

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?

The description adds significant meaning beyond the schema by explaining the union type in plain language: 'Pass string ID for one document' vs. 'Pass array of up to 10 IDs for comparison'. It also clarifies that the ID comes from search_docs results and gives usage context, which the raw schema description lacks.

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 and resource: 'Get complete document content' with 'DEEP DIVE' and 'unlimited size'. It clearly distinguishes itself from siblings like search_docs by positioning itself as the follow-up tool for full documents, and from get_code_examples and get_stats by focusing on complete content.

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?

Explicit usage patterns are provided, including single document, batch analysis, and a clear follow-up strategy after search_docs. It says 'Use after search_docs to get complete details of promising results' and 'Get full documents when search_docs snippets look promising but lack detail', which directly names the alternative tool and the contextual trigger.

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