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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the description need not repeat those. The description adds valuable behavioral context: the data accuracy contract (treat only returned fields as verified, avoid inference, label derived metrics) and the note that chart_render labels projected values as unverified_model_data. This goes beyond the annotations and clarifies expected data handling.

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 somewhat long but well-structured: it starts with a clear purpose, then gives usage directives (chart_render, ending phrase), and ends with a data accuracy contract. Each section serves a distinct purpose and is front-loaded with the most important information. It is not overly verbose given the complexity of the tool and the necessary behavioral instructions.

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 (7 actions) and lack of an output schema, the description should convey what the tool returns. It only mentions 'numeric values' generically and does not specify typical output fields or structure. The action descriptions in the schema cover what each action does, but not the return format. Thus, while the purpose is clear, the description leaves the agent uncertain about the exact data shape returned.

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%, with detailed descriptions for the action enum values and params object. The tool description itself does not add extra meaning beyond what the schema provides, so it meets the baseline for high schema coverage. No additional param semantics are needed.

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 performs cross-source analysis correlating Klaviyo email activity with web traffic, ecommerce revenue, and ad spend. It specifies the resource (email activity) and the analysis type, and distinguishes it from other connectors by focusing on email correlation. The mention of 'channel attribution, email-driven revenue, and unified marketing analytics' further clarifies its niche.

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 when-to-use context (channel attribution, email-driven revenue) and explicit instructions for when to call chart_render and how to end responses. However, it lacks explicit exclusions or differentiation from sibling tools like cross_source_ads_connector, so agents must infer when not to use this tool. The guidance is strong but not exhaustive.

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