Logpush MCP

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

With no annotations provided, the description carries full burden. It discloses the return format ('Dict with matching entries and count') and default behavior ('limit: Maximum entries to return (default 50)'). However, it doesn't mention important behavioral aspects like whether this is a read-only operation, potential rate limits, authentication requirements, pagination behavior, or what happens when no matches are found.

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 well-structured with clear sections (Args, Returns) and uses bullet-point style formatting. Every sentence adds value by explaining parameters or return values. While efficient, the opening line 'Search logs with filters.' is somewhat generic and could be more specific about the tool's unique value among siblings.

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 search tool with 9 parameters and no annotations, the description does well by documenting all parameters thoroughly and specifying the return format. Since there's an output schema (though not shown), the description doesn't need to detail return structure. The main gap is lack of behavioral context (rate limits, auth, etc.) and sibling differentiation, but parameter documentation is excellent.

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?

Given 0% schema description coverage, the description fully compensates by providing clear semantic explanations for all 9 parameters. Each parameter gets specific context: format requirements ('Date in YYYYMMDD format'), allowed values ('production or staging'), filtering logic ('Filter by exact HTTP status code'), comparison operators ('Filter by status code >= value'), search scope ('Search in URL and log messages'), and default values ('default 50'). This adds substantial value beyond the bare schema.

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 as 'Search logs with filters' which is a specific verb+resource combination. It distinguishes itself from siblings like 'get_errors', 'get_latest', or 'list_log_dates' by emphasizing search functionality with multiple filter parameters. However, it doesn't explicitly contrast with all siblings (e.g., 'read_log_file' might also involve log access).

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 like 'get_errors' (which might retrieve error logs specifically) or 'list_log_dates' (which might list available dates). There's no mention of prerequisites, performance considerations, or typical use cases that would help an agent choose between sibling tools.

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