derivation_solve_for

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 does state that the tool operates on the 'current expression' and that the result 'may have multiple solutions', which adds some behavioral context. However, it does not mention side effects such as recording a derivation step, modifying session state, or requiring an active session, leaving important behavioral traits undisclosed.

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 well-structured with a summary, parameter list, returns, and an example. It is slightly longer than necessary but every section contributes useful information, and the example is valuable for understanding the tool. The front-loaded summary clearly states the core action first.

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 (6 parameters, part of a derivation workflow) and the existence of an output schema, the description is reasonably complete. It covers all parameters, the return type (multiple solutions), and provides an illustrative example. However, it omits prerequisites such as requiring an active derivation session or previously loaded formula, which are important contextual details for correct 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 input schema provides no parameter descriptions (0% coverage). The description compensates fully by listing every parameter with a one-line meaning (variable, description, notes, assumptions, limitations) and includes a concrete example showing how to use variable, notes, and assumptions. This gives the agent clear semantic grounding for each argument.

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: 'Solve the current expression as a function of the specified variable.' This is a specific verb+resource combination that distinguishes it from sibling operations like integrate, differentiate, or simplify. The explicit mention of recording human knowledge (notes, assumptions) further differentiates it.

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 an example workflow (load formula then solve for a variable) which implies the intended use case, but it does not explicitly state when to use this tool versus alternatives like substitute or simplify. No exclusions or alternative tool names are given, so guidance remains implicit rather than explicit.

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