process_natural_language

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 describes the tool's function but lacks details on behavioral traits such as error handling, response format, rate limits, or any side effects. For a tool that processes and routes commands, this is a significant gap in transparency.

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 concise and front-loaded, with two sentences that directly state the tool's purpose and usage. Every sentence earns its place by providing essential information without redundancy or fluff, making it easy to understand 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 (processing natural language to route to other tools), no annotations, and no output schema, the description is minimally adequate. It covers the basic purpose and usage but lacks details on behavior, output, or integration with siblings, leaving gaps in completeness for effective agent use.

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?

The input schema has 100% description coverage, with the 'query' parameter well-documented as 'The natural language query to process into a tool call.' The description adds minimal value beyond this, mentioning 'takes a natural language query' but not elaborating on syntax or constraints. Baseline 3 is appropriate given the schema's thorough coverage.

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: 'Process natural language command and route to appropriate tool.' It specifies the verb ('process'), resource ('natural language command'), and outcome ('route to appropriate tool'). However, it doesn't explicitly differentiate from sibling tools like 'detect_thinking_directive' or 'should_think', which might also process language for specific purposes.

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 clear context: 'providing a way to interact with the MCP Agile Flow tools using natural language.' This indicates when to use it—for natural language interaction with the toolset. It doesn't explicitly state when not to use it or name alternatives among siblings, but the context is sufficiently clear for general usage.

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