Neotoma

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that corrections 'always win in snapshot computation,' which hints at priority and override behavior, but it lacks details on permissions, side effects, error handling, or response format. For a mutation tool with zero annotation coverage, this is a significant gap in transparency, though it does add some context beyond basic purpose.

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 highly concise and front-loaded: two sentences that directly state the tool's purpose and key behavior. Every sentence earns its place by adding value, with no wasted words or redundancy, making it efficient and well-structured.

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 (mutation with 6 parameters), no annotations, and no output schema, the description is incomplete. It covers the basic purpose and override behavior but lacks details on permissions, side effects, error handling, or return values. However, the 100% schema coverage helps offset some gaps, making it minimally adequate but with clear room for improvement.

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 all 6 parameters thoroughly. The description doesn't add any parameter-specific semantics beyond what's in the schema (e.g., it doesn't explain 'entity_type' or 'field' formats). Baseline 3 is appropriate as the schema does the heavy lifting, but the description doesn't compensate with extra insights.

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: 'Create high-priority correction observation to override AI-extracted fields.' It specifies the verb ('create'), resource ('correction observation'), and key behavior ('override AI-extracted fields'). However, it doesn't explicitly differentiate from siblings like 'update_schema_incremental' or 'store_structured', which might also modify data, so it misses full sibling differentiation.

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: 'Corrections always win in snapshot computation' suggests this tool is for overriding AI-extracted data in snapshot contexts. However, it doesn't provide explicit guidance on when to use this vs. alternatives like 'update_schema_incremental' or 'store_structured', nor does it specify prerequisites or exclusions, leaving usage somewhat implied rather than clearly defined.

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