Metro Logs 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 of behavioral disclosure. It mentions case-insensitive matching, which is useful, but omits critical details: whether this is a read-only operation, how results are ordered or limited, potential performance impacts, or what the output looks like. For a search tool with 5 parameters and no output schema, this leaves significant gaps in understanding its behavior.

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 a single, efficient sentence with zero wasted words. It's front-loaded with the core purpose and includes a useful behavioral note (case-insensitivity). Every element earns its place, making it easy for an agent to parse quickly.

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 (5 parameters, no output schema, no annotations), the description is insufficient. It lacks details on output format, result structure, error conditions, or operational constraints. While concise, it doesn't provide enough context for an agent to confidently invoke the tool without guessing about its behavior or results.

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 fully documents all 5 parameters. The description adds no parameter-specific information beyond implying text search functionality. This meets the baseline of 3, as the schema handles the heavy lifting, but the description doesn't enhance understanding of parameter interactions or use cases.

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: 'Search console logs for text (case-insensitive)'. It specifies the verb ('search'), resource ('console logs'), and a key behavioral trait (case-insensitive matching). However, it doesn't explicitly differentiate from sibling tools like 'get_logs' or 'clear_logs', which prevents a perfect score.

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 no guidance on when to use this tool versus alternatives. With sibling tools like 'get_logs' (which likely retrieves logs without filtering) and 'clear_logs' (which modifies logs), the agent receives no explicit or implied direction about appropriate contexts, prerequisites, or trade-offs for choosing this search function.

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