placements

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so safety is covered. The description adds useful non-annotation context by enumerating the returned detail (price, turnaround, authority, audience), which matters because there is no output schema. It still says nothing about error behavior for an unknown id, so it is not a full behavioral account.

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?

A single sentence with the scope and returned fields front-loaded; every clause earns its place and nothing is padded.

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 simple read-only single-record fetch with full annotation coverage and a fully documented parameter, the description is nearly sufficient. Since no output schema exists, listing the returned fields carries real weight, though the list is illustrative rather than a complete account of the response.

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?

Only one parameter, and the schema documents it at 100% coverage ("Outlet id returned by search_outlets"). The description's "by its id (from a search result)" adds provenance meaning but no format or syntax beyond what the schema already states, so the baseline 3 applies.

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?

"Full detail for a single outlet by its id" gives a specific verb+resource+scope, and the parenthetical "(from a search result)" plus the listed fields (price, turnaround, authority, audience) separate it from the sibling search_outlets, which returns search results rather than one record.

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 phrasing "by its id (from a search result)" establishes the intended workflow of retrieving a record produced by search_outlets, so the agent knows when to reach for this tool. It stops short of naming search_outlets explicitly or stating exclusions (e.g., when a search result already contains enough detail).

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, but the description adds real behavioral context beyond them: the total matches what the buyer is charged including volume tiers, no charge or order is created, the card is charged only at checkout, and it is refunded if the placement is unpublished or the turnaround is missed.

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-loads the return values and pricing guarantee, then follows with the non-charging and refund behavior. Every sentence carries information, though the final sentence on checkout/refund is slightly packed and could be tightened.

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 adequately covers return values (line items, discount, total, checkout_url) and the charging/refund lifecycle. Combined with annotations that cover the safety profile, nothing an agent needs to invoke this correctly 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 description coverage is 100% for the single 'items' parameter (with nested id/quantity documented and the max-30 limit stated), so the schema carries parameter semantics. The description refers to 'a set of outlets' but adds no syntax or semantics beyond what the schema already provides, making the baseline 3 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?

States a specific verb and resource ('Prices a set of outlets') and enumerates what it returns: line items, volume discount, final total, and a checkout_url. This clearly distinguishes it from the read-oriented siblings get_outlet and search_outlets, so an agent can pick it without opening a schema.

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 implies the use case (price a basket before purchase) and clarifies that it 'charges nothing and creates no order,' which steers the agent toward it for pre-checkout pricing. However it never names an alternative tool or states explicit when-not conditions, leaving usage to inference.

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

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuinely new behavioral context: the shape of the return (fixed USD price, turnaround, link disclosure, stable id) and the fact that the id is the handoff token for quote_placements. It stops short of describing pagination against limit/offset.

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?

Three tight sentences: what it searches, what it returns, and the one filter worth calling out. Zero filler and the primary purpose leads.

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 13-parameter read with no output schema, the description usefully summarizes the response fields an agent needs to reason about downstream. It is nearly complete, though it omits pagination behavior for limit/offset and the default result ordering.

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 92%, with each parameter (including enums like sort) already documented, so the schema carries the parameter burden. The description only restates max_price's budget-filtering role, which the schema already conveys. Baseline 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?

States a specific verb and resource (searches buyable media placements) and enumerates the filter axes it operates on: budget, authority, geography, topic and link policy. The scope ('buyable placements') cleanly separates it from get_outlet's single-outlet lookup and from quote_placements' pricing action.

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?

Usage is implied through the mention that max_price filters the catalogue to a budget and that the returned id is what quote_placements accepts, which gives an agent a sense of the workflow. However, it never states when to reach for get_outlet instead, nor any prerequisites or exclusions.

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