agentic-platform

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'get a pass/fail report with fixes' and 'No API key needed,' which adds useful context about output format and authentication. However, it lacks details on rate limits, error handling, or performance characteristics, leaving gaps for a mutation-like analysis tool.

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 stated first. The additional sentences ('The only MCP linter...' and 'No API key needed.') add value without redundancy. The 'Args:' section is structured but slightly informal; overall, it's efficient with minimal waste.

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 (analysis of JSON definitions), no annotations, and an output schema present, the description is reasonably complete. It covers purpose, parameter semantics, and output format ('pass/fail report with fixes'). However, it could benefit from more behavioral details like error cases or limitations, but the output schema mitigates this gap.

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 0%, but the description compensates well by explaining the single parameter: 'tools_json: Your MCP tool definitions as a JSON array or single object.' This adds clear meaning beyond the schema's basic type definition. Since there's only one parameter, the description effectively covers its semantics, though it could specify JSON structure examples.

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: 'Lint your MCP tool definitions for anti-patterns and missing fields.' It specifies the verb ('lint') and resource ('MCP tool definitions') with scope ('anti-patterns and missing fields'). However, it doesn't explicitly differentiate from sibling tools like 'agent_health_check' or 'check_usage', 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 some usage context by stating 'The only MCP linter that exists' and 'No API key needed,' which implies when to use this tool. However, it doesn't explicitly guide when to use this vs. alternatives like 'check_usage' or 'agent_health_check,' nor does it mention prerequisites or exclusions beyond the JSON input requirement.

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