Neotoma

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: the fallback to semantic search when no keyword match is found, and that it works across entity types unless specified. However, it doesn't mention performance characteristics, rate limits, authentication needs, or what happens with ambiguous matches.

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 appropriately sized with two sentences that are front-loaded: the first states the core functionality, and the second adds important behavioral context (fallback mechanism). There's no wasted text, though it could be slightly more structured with bullet points for clarity.

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 moderate complexity (2 parameters, no output schema, no annotations), the description is adequate but has gaps. It covers the basic operation and fallback behavior, but doesn't explain return values, error conditions, or how semantic search works. Without annotations or output schema, more detail on expected results would be helpful.

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 schema already documents both parameters thoroughly. The description adds marginal value by implying 'identifier' can include various types (name, email, tax_id) and that 'entity_type' is optional for filtering, but doesn't provide syntax or format details beyond what the schema states. Baseline 3 is appropriate when schema does the heavy lifting.

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 purpose with a specific verb ('retrieve') and resource ('entity'), and specifies the retrieval mechanism ('by identifier'). It distinguishes from sibling 'retrieve_entities' by focusing on identifier-based lookup rather than general retrieval. However, it doesn't explicitly contrast with 'retrieve_entity_snapshot' which might also retrieve entities.

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 by mentioning it works 'across entity types or specific type' and has a fallback to semantic search, which suggests when to use it (for identifier-based lookups with fuzzy matching). However, it doesn't explicitly state when NOT to use it or name alternatives among siblings like 'retrieve_entities' for broader queries.

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