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

Annotations only provide hints (readOnlyHint=false, destructiveHint=false), but the description adds substantial behavioral context: rate limiting ('5 per identifier per day'), quota exemption ('doesn't count against your tool-call quota'), anonymous usage with a claim_token for later retrieval, and the human review process ('team reads digests daily'). No contradiction with 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 longer than average but every sentence serves a purpose: definition, use cases, exclusions, claim_token mechanics, rate limits, and quota. It is well-structured with clear logical flow. It could be tightened slightly (e.g., the 'Not sure?' sentence is somewhat redundant with the exclusion sentence) but remains highly readable and front-loaded.

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?

Despite lacking an output schema, the description fully covers the return behavior (claim_token, how to poll for resolution) and all important contextual details (rate limits, quota, what constitutes appropriate feedback). It addresses the nested `context` object and enum values implicitly through examples. This is complete for a feedback 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?

Input schema covers 100% of parameters with descriptions, so baseline is 3. The description adds extra semantics beyond the schema, particularly for claim_token (demonstrating the call pattern `pipeworx_feedback({claim_token:"pwfb_…"})` and the constraint 'with no other arguments') and for context (describing pack/tool/vertical as 'Optional structured context'). This goes beyond what the schema provides, justifying a 4.

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 opens with a specific verb+resource: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It clearly distinguishes this from sibling tools (all information/research tools) by framing it as a feedback channel for the Pipeworx toolset itself.

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?

Provides explicit when-to-use criteria ('Use when a tool returns wrong/stale data (bug)... feature/data_gap... praise') and equally explicit when-not-to-use guidance ('ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server... file it with that server instead'). It also gives a disambiguation strategy ('Pipeworx tool names are the ones this connection lists').

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