Semantic search SGU episodes

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

Without annotations, the description carries full burden. It explains the hybrid ranking approach (vector + keyword via RRF), the requirement of an embedding index, and the default provider. However, it does not detail failure modes (e.g., if index missing) or edge cases, leaving some behavioral 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 concise (5 sentences) with the key purpose front-loaded. Every sentence adds distinct value: purpose, usage alternatives, algorithm overview, prerequisites, and configuration. No redundancy or fluff.

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 (hybrid search with 3 parameters and a prerequisite index), the description covers purpose, usage, parameters, and prerequisites adequately. It mentions return fields (title, date, theme, score) but lacks detailed return structure or error handling. Still, it is complete enough for an experienced agent.

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 coverage is 100%, so baseline is 3. The description adds value by providing natural language examples for 'query', explaining default 'limit' (10), and describing 'mode' options with clear interpretations. This goes beyond the schema's basic descriptions.

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 concept-level semantic search on episodes, using natural language queries. It explicitly distinguishes itself from sibling tools that search for exact words (search_episodes/search_segments), making its purpose unambiguous.

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 explicit guidance on when to use this tool ('for fuzzy, conceptual questions') and when to prefer alternatives ('prefer search_episodes/search_segments for exact words'). It also mentions a prerequisite (embedding index) and configuration (EMBED_PROVIDER), aiding correct invocation.

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