Favro 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 that the tool 'Returns: The created comment metadata,' which adds some context about the output. However, it fails to disclose critical behavioral traits such as whether this is a mutation (implied by 'Add'), permission requirements, rate limits, or error handling. For a tool with no annotations, this is insufficient.

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, starting with the core purpose. The 'Args' and 'Returns' sections are structured efficiently, with each sentence adding value. However, the formatting as a block of text could be slightly improved for readability, and some redundancy exists (e.g., repeating 'card' details).

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 (3 parameters, mutation operation) and the presence of an output schema (which covers return values), the description is partially complete. It explains parameters and the return concept but lacks details on behavioral aspects like permissions or errors. With no annotations and moderate complexity, it should do more to be fully adequate.

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 0%, so the description must compensate. It adds meaningful semantics beyond the schema by explaining parameter purposes: 'card' can be ID, sequential ID, or name; 'comment' is text to post; 'board' is needed for name lookup and optional for sequential ID. This clarifies usage but does not cover all potential edge cases or formats, preventing a perfect score.

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: 'Add a comment to a card.' It specifies the verb ('Add') and resource ('comment to a card'), making the action unambiguous. However, it does not explicitly differentiate from sibling tools like 'update_card' or 'tag_card' in terms of when to use each, 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 implied usage context by mentioning when the 'board' parameter is needed (for name lookup vs. sequential ID), but it does not explicitly state when to use this tool versus alternatives like 'update_card' for editing comments or other sibling tools. No clear exclusions or alternatives are named, leaving gaps in guidance.

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