lingo_solve

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

With no annotations, the description carries the full burden, and it does substantial work: it discloses the exact solution payload (status, objective, variables with reduced costs, slack/surplus with duals) and the auto-wrapping behavior of MODEL:/END. It stops short of disclosing failure handling (infeasible/unbounded models) or the dependency on a LINGO engine/license being available.

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?

Three sentences, front-loaded with the solve action, then input forms, then the wrapping caveat. Every sentence carries distinct information and the most decision-relevant fact leads.

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?

For a 4-param tool with no output schema and no annotations, the description is largely complete: it covers both input modes and compensates for the absent output schema by naming the returned fields. It omits error/solver-failure semantics, which are relevant for a solver tool.

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 coverage is 100%, so the baseline is 3; the description exceeds it by clarifying that 'model' can be written without MODEL:/END wrappers, which is genuine parameter behavior the schema does not state. It adds nothing extra for timeout_ms or nonzero_only, which the schema already documents.

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?

States a specific verb and resource ('Solve a LINGO optimization model') and enumerates the output it produces. It is clearly distinguishable from siblings like lingo_run_commands and lingo_status, though it does not name any sibling explicitly to route between them.

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?

Usage is only implied: the agent can infer this is the tool to solve a model, and the two input forms (inline source vs .lng/.lg4 path) are noted. There is no explicit when-to-use/when-not guidance or comparison to lingo_run_commands, which an agent might confuse for a way to execute a model.

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