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

Annotations already indicate non-readonly, open-world, non-idempotent behavior. The description adds specific pipeline steps (AI summary, auto-quote, auto-schedule, SMS, team notify) and tagging behavior, which provides useful behavioral context beyond what annotations offer. However, it does not disclose failure modes or authorization needs.

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 front-loads the purpose and efficiently lists the pipeline steps. No extraneous information.

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?

The description gives a good high-level overview of the pipeline stages and output tagging. However, it omits prerequisites (e.g., lead must exist) and conditional behavior, which would improve completeness given the tool's complexity.

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 coverage is 100%, baseline 3. The description adds meaning by linking 'auto-quote' and 'auto-schedule' steps to the corresponding boolean parameters, and 'ad campaign attribution' to the adCampaign parameter. This provides practical context beyond the schema descriptions.

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: processing a Google Ads lead through a full zero-touch pipeline with specific steps listed. It distinguishes itself from sibling tools like 'workflows.process_lead' by specifying the Google Ads context and pipeline stages.

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 clear context about when to use this tool (for Google Ads leads needing full automated processing) but does not explicitly rule out alternatives or mention when not to use it. The absence of exclusionary guidance prevents a perfect score.

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