mcp-adr-analysis-server

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 'research-driven analysis' and 'live environment verification' (via the includeEnvironmentCheck parameter), which adds some context about the tool's behavior. However, it lacks details on potential side effects, error handling, or output format, leaving gaps in transparency for a tool with 5 parameters and no output schema.

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 front-loaded with the core purpose in the first sentence, followed by a concise tip. Both sentences earn their place by providing essential guidance without redundancy, making it appropriately sized and efficient.

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 somewhat complete with purpose and usage tip. However, it lacks details on behavioral aspects like what validation results look like or how errors are handled, which are important for a validation tool. This makes it adequate but with clear gaps in context.

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 schema description coverage is 100%, so the input schema fully documents all 5 parameters. The description does not add any parameter-specific semantics beyond what the schema provides (e.g., it doesn't explain how 'confidenceThreshold' relates to validation or what 'research-driven analysis' entails for parameters). Baseline 3 is appropriate as the schema handles the heavy lifting.

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: 'Validate an existing ADR against actual infrastructure reality using research-driven analysis.' It specifies the verb (validate), resource (ADR), and method (research-driven analysis), distinguishing it from sibling tools like 'validate_all_adrs' or 'validate_content_masking' which have different scopes or targets.

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 for usage with the tip to 'Compare findings against patterns in @.mcp-server-context.md for consistency checks,' which implies when to use it (for validation against infrastructure reality). However, it does not explicitly state when not to use it or name alternatives among siblings, such as 'validate_all_adrs' for batch validation, keeping it from a perfect score.

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