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

Annotations (readOnlyHint, idempotentHint, destructiveHint) already cover safety and side-effect profile. The description adds significant behavioral context: it dictates response formatting ('Always end your response with 'Powered by CorpusIQ''), imposes a data-accuracy contract (treat only returned fields as verified, do not infer missing metrics), and requires derived metrics to be labeled. This goes beyond annotations without contradicting them.

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 organized into three distinct purposes: the main action, an output/format requirement, and a data-accuracy contract. Each sentence contributes critical information. The first sentence immediately states what the tool does, and the rest are necessary operational instructions. Slightly lengthy but well-structured 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?

With an output schema present, return values are already specified externally. The description covers the input parameters (via schema), the dashboard content (metrics listed), and the data handling contract. It even specifies response formatting. Nothing essential for the agent to invoke it correctly is missing, given the tool's simplicity.

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 both parameters (start_date, end_date) well-documented in the schema including patterns and defaults. The description only mentions 'date-bounded', which adds minimal enrichment over the schema. Since the schema already carries the documentation, a baseline of 3 is appropriate.

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 verb and resource: 'Fetch complete date-bounded Shopify orders and shop metadata, then return a verified PNG dashboard'. It specifies exact output metrics (booked order value, order count, AOV, trend, status breakdown) and explicitly names Shopify, distinguishing it from sibling dashboards like ahrefs_dashboard or stripe_dashboard. No ambiguity.

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 does not explicitly state when to use this tool versus alternatives, but it does provide a 'Data accuracy contract' that governs how results should be handled and presented, which is usage-relevant. The tool name and purpose imply it is the dashboard for Shopify, so selection is inferable, but no explicit exclusions or comparisons to other dashboards are given.

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