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report_problem

Report issues and errors to the LMCP team for prompt support and resolution.

Instructions

Report a problem to the LMCP team

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • server.js:102-102 (registration)
    Tool 'report_problem' is registered in the TOOLS array at index position matching line 102, with description 'Report a problem to the LMCP team'.
    ["report_problem", "Report a problem to the LMCP team"],
  • Handler logic for all tools including 'report_problem': each tool is registered via server.tool() with an empty schema and a stub async handler that returns an inspection message.
    for (const [name, desc] of TOOLS) {
      server.tool(name, desc, {}, async () => ({
        content: [{ type: "text", text: "This is an inspection stub. Install Local MCP: npx -y local-mcp@latest setup" }],
      }));
    }
Behavior2/5

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

The description does not disclose behavioral traits beyond the action itself. There are no annotations, so the description carries the full burden, but it only states the purpose without detailing side effects, logging, or any constraints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that directly conveys the tool's purpose. It is concise and front-loaded, though it could potentially include a bit more detail without losing conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simplicity (no parameters, no output schema), the description is minimally complete. However, it lacks any indication of expected outcomes or additional context that might help an agent decide when to use the tool effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has zero parameters and is fully covered (100%). The description adds no parameter meaning because none exist, but the baseline for no parameters is 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'report' and the resource 'a problem to the LMCP team', making the tool's purpose unambiguous. It distinguishes itself from siblings, as no other tool reports problems.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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, such as when a user wants to provide feedback or report an issue. The context signals show no siblings with similar purpose, but the lack of usage context reduces clarity.

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

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