Agent Feedback Loop

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full disclosure burden. It effectively explains the side effect ('build a quality database') but lacks details on mutation behavior, idempotency, whether reports can be updated, or what confirmation/response occurs after submission.

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?

Structure is optimal: front-loaded summary ('Report the result...'), followed by value proposition ('Helps build...'), then detailed Args block. Every sentence earns its place with no redundancy or filler.

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 7 parameters with zero schema descriptions, the description successfully documents all inputs. Minor gap: without output schema or description of return values/confirmation, the agent doesn't know what to expect after submission, though this is less critical for a reporting tool.

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?

Despite 0% schema description coverage, the description compensates perfectly via the 'Args:' block which documents all 7 parameters (tool_name, success, quality_score, task_description, server_name, response_time_ms, error_message) with clear semantics and examples (e.g., '10 = perfect' for quality_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 'Report[s] the result of using an MCP tool' with the specific purpose of building 'a quality database so agents can discover which tools work best.' It distinguishes sharply from sibling retrieval tools (get_best_tools, get_tool_quality, get_trending_tools) by being the only submission/feedback tool.

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?

While it doesn't explicitly state 'when-not' rules, the description establishes clear context through the database-building explanation, implying this should be used after tool execution to contribute quality data. The verb 'Report' clearly contrasts with siblings' 'get' operations, making the usage context obvious without explicit enumeration of alternatives.

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