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

Annotations already declare readOnlyHint=true and idempotentHint=true, but the description adds substantial behavioral detail: it specifies that reads, lifecycle exits (disconnect, unsubscribe, cancellation), and the settling sale path are never priced; it explains the pricing curve format and that reprices are effective-forward. This goes well beyond what annotations provide, and no contradictions exist.

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 dense but every sentence carries meaningful information: the purpose, the pricing format, exemptions, the effective-forward policy, the source of truth, and a return structure example. It is front-loaded with the main idea and structured logically. No filler or redundancy.

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 no output schema, the description must document the return format, and it does: a detailed object with title, peg, live, take_rate, price_form, lifecycle, failure_modes, and platforms. It also includes an example call. Given the simplicity of the tool (no parameters), this is fully complete for an agent to invoke and interpret results.

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 tool has zero parameters, so schema coverage is trivially 100%. Per the rubric, 0 params merits a baseline of 4. The description doesn't need to explain parameters and instead focuses on the return structure, which is appropriate. No further semantic augmentation is 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 opens with a clear statement of purpose: 'The federation pricesheet — every platform's per-act Com prices.' It identifies the resource (pricesheet) and the action (read). It also distinguishes itself from sibling tools by focusing specifically on pricing rather than catalog searches or other federation operations, making the uniqueness obvious.

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 explains when this tool is useful (to look up per-act costs) and adds context like 'Any tool not listed is free' and 'the price you read is the price applied.' It does not explicitly name alternatives or exclusions, but the context is sufficient for an agent to infer when to call it. A clear 'use this when you need pricing details' statement would push it to 5.

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