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

The readOnlyHint annotation already indicates a safe read operation. The description adds valuable behavioral context beyond the annotation: the empty snapshot response behavior and the content structure. This helps the agent understand what to expect in edge cases.

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 concise and front-loaded. The first sentence states the purpose and output fields, the second sentence covers an important edge case, and the third line defines the parameter. No wasted words.

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 simplicity (one parameter, output schema present, readOnly annotation), the description covers all essential aspects: purpose, parameter, and a significant behavioral nuance. The output schema handles return value details, so no additional explanation is needed.

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?

The schema has 0% description coverage, so the description must compensate. It provides 'slug: provider slug,' which clarifies the parameter's meaning but adds minimal detail beyond the schema's property name. For a single simple parameter, this is adequate but not rich.

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 action: 'Get demand/popularity snapshot for a provider' and lists the response fields (computed_at, metrics, top_slots). It distinguishes itself from siblings like get_slot_demand by focusing on provider-level demand. The verb and resource are specific.

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 what the tool returns and includes a notable edge-case behavior (empty snapshot returns 200 with nulls, not 404). However, it does not explicitly mention alternatives or when-not-to-use, though the purpose is clear enough to infer usage.

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