get_docs

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

With no annotations provided, the description carries the full burden. It explains the workflow: pulling sessions, filtering, returning relevant chunks, and requiring optional 'rag' extra. It does not disclose auth needs, rate limits, or side effects, but it provides reasonable behavior details.

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: a one-line summary, then a detailed explanation, followed by the 'rag' extra note, and finally an args list. It is front-loaded and every sentence adds value without redundancy.

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 (5 parameters, semantic search) and the presence of an output schema, the description covers the key aspects: purpose, workflow, parameter meanings, and special requirements. It does not detail the output format but that is handled by the 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 0%, so the description must add meaning. It provides brief but helpful descriptions for each parameter (e.g., 'user_question: What you want to learn (used for the similarity search)', 'website_id: The website id (from get_websites)'). This adds value beyond the bare 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 it performs 'Semantic search over many user journeys to surface the most relevant moments', using specific verbs and resources. It distinguishes from sibling tools like get_tracking_data or get_session_ids by focusing on relevance-based search rather than raw data retrieval.

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 provides clear context on when to use: for analyzing behavior across many users without overflowing context. It mentions the optional 'rag' extra requirement. However, it does not explicitly state when not to use or compare to alternatives, leaving some ambiguity.

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