langfuse-mcp

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 discloses that the tool retrieves data (implied read-only) and describes output behaviors based on 'output_mode', including file-saving for 'full_json_file'. However, it lacks details on error handling, rate limits, authentication needs, or data sensitivity, leaving gaps in behavioral context.

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 appropriately sized and front-loaded with the core purpose in the first sentence. The structured 'Args' and 'Returns' sections are clear but slightly verbose; every sentence earns its place by adding necessary details, though it could be more streamlined without losing essential information.

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 has an output schema (implied by 'Returns' section), the description does not need to explain return values in detail. It covers the purpose, parameters, and output modes adequately. However, for a tool with no annotations, it could benefit from more behavioral context like error cases or permissions, keeping it from a perfect score.

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 description coverage is 100%, so the schema already documents parameters well. The description adds value by explaining the 'ctx' parameter's purpose (context with Langfuse client) and clarifying the 'output_mode' effects on returns, which enhances understanding beyond the schema's enum descriptions. It does not fully compensate for all semantic nuances, but provides useful context.

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 with a specific verb ('Get') and resource ('a single observation by ID'), distinguishing it from sibling tools like 'fetch_observations' (plural) and 'fetch_sessions'. It precisely defines the scope as retrieving one observation using its unique identifier.

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 implies usage context by specifying it fetches 'a single observation by ID', suggesting it should be used when you have a specific observation ID rather than for listing multiple observations. However, it does not explicitly state when not to use it or name alternatives like 'fetch_observations' for bulk retrieval, which would elevate the score to 5.

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