pyfastmail-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 states the tool searches emails and returns specific fields, but lacks critical details: whether it's read-only (implied but not stated), permissions required, rate limits, pagination behavior beyond 'limit', error handling, or what happens with large result sets. For a search tool with zero annotation coverage, this is a significant gap.

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 and appropriately sized: a clear purpose statement followed by a parameter list with concise explanations. Every sentence adds value, and it's front-loaded with the core functionality. Minor room for improvement in flow, but overall 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 (7 parameters, search functionality) and lack of annotations, the description is moderately complete. It covers parameters well and mentions return fields, but since an output schema exists, it doesn't need to detail return values. However, it misses behavioral aspects like search scope (e.g., all mailboxes vs. specific ones) and error cases, leaving gaps for a tool with no annotations.

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%, so the description must compensate. It lists all 7 parameters with brief explanations (e.g., 'Full-text search query' for 'text', 'Filter by sender address' for 'from_'), adds default values for 'limit' and 'newest_first', and clarifies optional filtering. This provides meaningful context beyond the bare schema, though it could elaborate on parameter interactions or format specifics.

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: 'Search emails with optional filters. Returns id, subject, from, date.' It specifies the verb ('Search'), resource ('emails'), and return fields. However, it doesn't explicitly differentiate from sibling tools like 'mail_get_recent_emails' or 'mail_get_email_thread', which are also email retrieval tools.

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. It doesn't mention sibling tools like 'mail_get_recent_emails' (for recent emails without search) or 'mail_get_email_thread' (for thread-based retrieval), nor does it specify prerequisites, scopes, or exclusions. Usage is implied but not articulated.

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