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

Annotations already provide key behavioral hints (read-only, open-world, idempotent, non-destructive). The description adds valuable context beyond annotations: it specifies the 'limit' parameter's max (100) and default (20), describes error handling ('Project not found', 'Authentication failed'), and outlines the return format options ('json' vs 'markdown'). This enhances transparency without contradicting 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 well-structured with clear sections (Args, Returns, Use Cases, Error Handling) and front-loaded purpose. It's appropriately sized for a tool with 9 parameters, though some redundancy exists between 'Args' and the schema. Every sentence adds value, but it could be more concise by avoiding duplication of schema 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 (9 parameters, no output schema) and rich annotations, the description is mostly complete. It covers purpose, usage examples, error handling, and parameter details. However, without an output schema, it could better describe the structure of returned feedback items (e.g., fields like 'customer info', 'timestamps') to fully compensate for the missing structured output definition.

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 100%, so the schema already documents all parameters thoroughly. The description's 'Args' section repeats parameter information but adds minimal extra semantics (e.g., clarifying 'organized_state' values). This meets the baseline of 3 since the schema does the heavy lifting, but the description doesn't significantly enhance understanding beyond what's in the schema.

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 and filter customer feedback in a LaunchNotes project.' It uses specific verbs ('search', 'filter') and identifies the resource ('customer feedback'), distinguishing it from sibling tools like 'launchnotes_get_feedback' (which likely retrieves specific feedback) and announcement-focused 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 'Use Cases' section provides clear examples of when to use this tool (e.g., 'What are customers saying about Digests?', 'Show me all unhappy feedback'), which implicitly guides usage. However, it doesn't explicitly state when NOT to use it or name alternatives like 'launchnotes_get_feedback' for retrieving specific feedback by ID rather than searching/filtering.

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