Feedbucket 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 indicates this is a read operation ('get') and describes the output content (statistics breakdowns), but doesn't cover aspects like performance characteristics, error conditions, or data freshness. The description doesn't contradict any annotations, but it's moderately informative given the lack of structured annotations.

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 a single, well-structured sentence that efficiently conveys the tool's purpose and output scope. It's front-loaded with the core action ('get a quick summary') and lists key statistics without unnecessary elaboration. However, it could be slightly more concise by avoiding the dash list format, but overall it's highly 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 simplicity (0 parameters, no output schema, no annotations), the description is reasonably complete for a read-only statistical tool. It specifies what statistics are returned, which compensates for the lack of output schema. However, it doesn't address potential behavioral nuances like data scope (e.g., all projects vs. current project) or update frequency, leaving some contextual gaps.

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 tool has 0 parameters with 100% schema description coverage, so the schema already fully documents the absence of inputs. The description adds no parameter-specific information, which is appropriate here. Baseline for 0 parameters is 4, as the description doesn't need to compensate for any gaps in parameter documentation.

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 with specific verbs ('get a quick summary') and resources ('project feedback statistics'), including breakdowns by status, type, and recent activity. It distinguishes itself from siblings like feedback_get or feedback_list by focusing on aggregated statistics rather than individual feedback items or lists. However, it doesn't explicitly contrast with all siblings (e.g., api_status).

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 implies usage context through 'quick summary' and the statistical nature of the output, suggesting it's for overview purposes rather than detailed inspection. However, it lacks explicit guidance on when to use this tool versus alternatives like feedback_list (which might provide raw data) or feedback_get (for specific items), and doesn't mention prerequisites or exclusions.

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