triple_vector_product

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

No annotations are provided, so the description carries full burden for behavioral disclosure. The description only states what is calculated, with no information about input validation (e.g., vector dimensions, numeric format), error handling, performance characteristics, or output format. For a mathematical tool with three vector parameters, this lack of behavioral context is inadequate.

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 extremely concise and front-loaded with the core purpose in a single sentence. Every word earns its place: 'Calculate' (verb), 'triple vector product a×(b×c)' (specific operation), and 'Domain: linear_algebra.vectors, Category: general' (context). There is zero wasted text or 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 complexity (mathematical operation with three vector inputs), lack of annotations, 0% schema description coverage, and no output schema, the description is severely incomplete. It doesn't address input requirements, output format, error conditions, or mathematical assumptions (e.g., vector dimensionality). For a tool with three undocumented parameters, this is inadequate.

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%, meaning none of the three parameters (vector_a, vector_b, vector_c) have descriptions in the schema. The tool description adds no parameter semantics beyond naming them in the mathematical expression 'a×(b×c)'. It doesn't explain what constitutes valid vectors (e.g., numeric arrays, required dimensions, format expectations), leaving parameters completely undocumented.

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: 'Calculate the triple vector product a×(b×c)', specifying the mathematical operation and domain (linear_algebra.vectors). It distinguishes from sibling tools like 'cross_product' and 'triple_scalar_product' by focusing on the specific triple vector product operation. However, it doesn't explicitly differentiate from all siblings beyond naming the operation.

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 minimal usage guidance. It mentions the domain (linear_algebra.vectors) and category (general), but gives no explicit when-to-use instructions, no prerequisites, and no comparison to alternatives like 'cross_product' or 'triple_scalar_product'. The agent must infer usage from the operation name alone.

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