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

Annotations already establish readOnly/idempotent/non-destructive, and the description goes well beyond them: it discloses the rate limit (60 calls per minute per key or person), that the call is free, that output is uniform across readers, that metered AI steps such as Cinematic Ads analysis and export are excluded, and how to derive real per-run cost via meta.cost_basis.effective_cents_per_credit. It also documents the CSV alternate endpoint.

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 lead sentence front-loads what the tool is and the price-option granularity, and every clause afterwards (auth, rate limit, field meanings, cost math, CSV) carries information. It is dense and delivered as one long block rather than structured sections, which makes the output-field enumeration harder to scan than a list would be.

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 takes on the burden of documenting the return shape and does so field by field: feature, output_kind, model_id, provider, resolution, with_sound, unit, list_credits_per_unit and list_usd_per_unit, plus the credit-to-dollar conversion. Auth, rate limits and known omissions are all covered, leaving nothing an agent needs to call it correctly.

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% for the single workspace_id parameter, so the baseline is 3. The description adds meaning by tying the id to auth paths ('the workspace the reporting key belongs to, or one you are a member of') and noting that the reporting key must be minted by that workspace's Owner, which clarifies what a valid value looks like.

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 resource and scope: the workspace's catalogue of sellable services, one row per price option, including feature, model, provider, resolution and unit prices. That distinguishes it from list_models (model catalogue) and get_usage_summary (spend), though it never names those siblings explicitly. An agent can infer the purpose confidently from the field list.

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?

Prerequisite context is strong: it says a wdr_report_ key or Owner/Admin/Member sign-in is required and that the result is identical for every reader. However it never states when to call this versus list_models, get_usage_summary or get_workspace_budget, and gives no exclusions beyond 'metered AI steps are not listed'. Usage is implied rather than routed.

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