taylor_series

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

No annotations are provided, so the description carries the full burden. It mentions the domain (numerical) and category (series), but does not disclose critical behavioral traits such as input format for the function 'f' and 'derivatives', error handling, computational limits, or output format. This leaves significant gaps for an AI agent.

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 front-loaded with the core purpose. It uses only one sentence with no wasted words, making it efficient. However, the domain/category parenthetical adds little value and could be integrated more smoothly.

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 (5 required parameters, 0% schema coverage, no annotations, no output schema), the description is incomplete. It does not compensate for the lack of structured data, failing to explain parameters, behavior, or output. This makes it inadequate for reliable tool invocation.

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 description coverage is 0%, and the description does not explain any of the 5 required parameters ('f', 'derivatives', 'a', 'x', 'n'). It fails to add meaning beyond the schema, leaving parameters completely undocumented. For example, it does not clarify that 'derivatives' should be an array of derivative expressions or what 'n' represents (order of expansion).

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 states the tool computes a Taylor series expansion of a function around a point, which is a clear purpose. However, it does not differentiate from sibling tools like 'maclaurin_series' (which is a special case of Taylor series) or 'power_series', making it somewhat vague in context. The domain/category tags add minimal value.

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?

No guidance is provided on when to use this tool versus alternatives. For example, it does not mention when to prefer 'taylor_series' over 'maclaurin_series' (which expands around zero) or other series tools like 'sin_series' or 'cos_series'. The description lacks any context for selection.

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