List the example optimization models bundled in LINGO's Samples folder, optionally filtered by name, to help you locate sample files.
List the example models shipped in the LINGO Samples folder, optionally filtered by name.
| Name | Required | Description | Default |
|---|---|---|---|
| filter | No | Case-insensitive substring to filter sample names. |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It conveys an implicitly safe, read-only listing operation and scopes it to the shipped Samples folder, but it says nothing about permissions, the shape of returned entries, ordering, or whether the list is paginated.
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?
A single front-loaded sentence with the resource stated first and the optional filter trailing. No filler 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?
For a one-parameter, no-output-schema listing tool this is largely sufficient: it identifies the source folder and the filter behavior. The only gap is that return format and ordering are unspecified, which is minor given the tool's simplicity.
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?
There is a single parameter with 100% schema description coverage, so the schema already explains the case-insensitive substring filter. The description's 'optionally filtered by name' merely confirms optionality without adding syntax or matching-behavior detail beyond the schema; baseline 3 is appropriate.
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 names a specific verb (List) and resource (example models in the LINGO Samples folder), so the agent knows exactly what the tool returns. It does not explicitly differentiate itself from the sibling tools (lingo_solve, lingo_run_commands, lingo_status), but the resource is distinct enough to be told apart.
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: an agent can infer this is a discovery step for finding shipped example models, but there is no explicit when-to-use statement, no when-not-to-use condition, and no mention of the sibling tools it complements. The only guidance is the optional filter, which is really a parameter note.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.