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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds genuinely non-obvious behavior: fixed pack sizes per network (5 for LinkedIn/Facebook, 8 for the rest) and a flat 1 Creative Credit charge regardless of what the user asked for. It stops short of describing the full return shape beyond the `credits` field.

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?

Front-loaded with the core action, then pricing rules, then the parameter default, then the downstream handoff — a sensible order with no filler. It is dense to the point of terseness in places ("even if they asked for one" requires inference), costing a point.

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?

For a read-only pricing tool with only one required parameter, this covers the pricing model, the platform default, and the downstream contract with create_content_pack. With no output schema, more detail on the returned object beyond `credits` would have been useful, but nothing essential is missing.

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%, so the baseline is 3, but the description goes beyond it by explaining the consequences of omitting `platform` (resolve to the brand's home network) and by warning against defaulting to LinkedIn. That is real decision-relevant meaning the enum alone does not convey.

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?

"Price a pack of posts for one network without writing them" names a specific verb (price/quote), a specific resource (a pack of posts), and explicitly marks the boundary against content generation. Against the sibling create_content_pack, an agent can immediately tell this one only estimates cost.

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?

It clearly frames the pre-creation workflow by saying the returned `credits` must be submitted as `expected_credit_cost` on create_content_pack, which effectively names the follow-up tool. It also gives a negative guidance for platform ("never invent LinkedIn"). It lacks an explicit "call this before creating" statement, so it is strong context rather than a full when/when-not rule set.

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