Featurebase MCP 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 lists available fields but doesn't explain key behaviors: whether this is a read-only operation, if it requires authentication, how pagination works (implied by limit/page but not described), error handling, or rate limits. The field list adds some context but misses critical operational details for a tool with 9 parameters.

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 but becomes overly verbose by listing all available fields twice (including nested replies). This repetition (e.g., field names duplicated for replies) adds unnecessary length without enhancing clarity. A more concise approach would summarize field categories or refer to documentation.

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 (9 parameters, no output schema, no annotations), the description is incomplete. It lacks information on return format, error cases, authentication needs, and behavioral constraints. While it covers fields and basic purpose, it doesn't provide enough context for safe and effective use by an AI agent, especially for a data retrieval tool with filtering options.

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 schema already documents all 9 parameters thoroughly. The description adds value by listing available return fields (e.g., upvoted, content, replies), which helps interpret the 'select' parameter, but doesn't provide additional semantic context beyond what the schema offers. This meets the baseline of 3 for high schema 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: 'Get comments for a post or changelog.' It specifies the resource (comments) and the target objects (post or changelog). However, it doesn't explicitly differentiate from sibling tools like 'get_post_upvoters' or 'list_posts,' which reduces the score from a perfect 5.

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 prerequisites (e.g., needing a post or changelog ID), compare to siblings like 'list_posts' for post retrieval, or specify use cases (e.g., filtering vs. fetching all comments). This lack of contextual direction leaves the agent to infer usage.

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