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

With no annotations provided, the description carries the burden of disclosing behavior. It states that 'Descendants are returned as a nested tree for both relationship types' and 'Ancestors are returned as a nested chain, filtered to nervous system terms for part_of.' It also implies the default direction and depth behavior via 'Start with max_depth=1' and 'offer to go deeper.' These details go beyond the schema and help the agent anticipate the output structure.

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 and well-structured. It opens with the core action, then gives relationship guidance, describes return formats, and ends with a practical usage tip. Each sentence earns its place, and there is no filler. It is appropriately sized for the tool's complexity.

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?

Despite having no output schema, the description covers all key aspects: what the tool does, when to use each relationship, the shape of the returned data (tree vs. chain), and a recommendation for default depth. Combined with the detailed parameter descriptions in the schema, the agent has enough information to select and invoke the tool effectively.

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 schema already provides 100% coverage with descriptions for all 4 parameters, so the baseline is 3. The description adds meaningful context: it explains how 'relationship' maps to use cases (part_of for regions, subclass_of for cells), gives example IDs in the schema, and clarifies that direction and max_depth control the output structure. This enriches the parameter definitions beyond the 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 the tool's function: 'Build a hierarchy tree for a VFB term, showing ancestors (parents) and/or descendants (children).' It uses a specific verb ('Build') and resource ('hierarchy tree for a VFB term'), and it distinguishes itself from sibling tools by focusing on hierarchy exploration. It also includes concrete examples like 'what are the parts of the mushroom body?' which reinforces the purpose.

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 gives explicit guidance on when to use each relationship: '"part_of" for brain region structure' and '"subclass_of" for cell type hierarchies', with examples for each. It also advises starting with 'max_depth=1 for direct parents/children' and offering to go deeper. While it doesn't explicitly state when not to use this tool or name alternatives, the usage context is clear and actionable.

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