get_meta_opportunity_score

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

With no annotations, the description carries the burden and does well: it names the underlying Marketing API edge (/act_<id>/recommendations), discloses the auth model ('client's stored access token'), and describes the normalized return shape. It does not state whether the call is read-only or how large the recommendation queue can get, but for a read-style score endpoint the disclosure is above par.

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 what is returned, then the mechanics, then the use cases; no filler sentences. It is slightly dense with parenthetical detail, but every clause carries information.

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?

There is no output schema, and the description compensates by listing the normalized fields of each recommendation and the score range. It stops short of explaining how to interpret the 0–100 scale, empty queues, or partial-failure behavior, leaving a small gap for a two-parameter aggregation tool.

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% — client_id points at list_clients in the schema and ad_account_ids documents its override behavior — so the schema does the heavy lifting. The description adds only the implicit link that the stored access token is resolved via the client, not new per-parameter semantics. 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?

States a specific verb and resource — Meta's account-level Opportunity Score plus the recommendations queue — and enumerates the recommendation categories covered. It is clearly distinguishable from the sibling performance/auction/anomaly tools, which return metrics rather than scores and recommendations.

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?

Explicitly enumerates three usage contexts: scoring an account quickly, feeding recommendations into a Meta audit, and prioritising high-lift fixes. Strong positive guidance, but it names no alternatives or when-not conditions (e.g., when to prefer the performance tools instead).

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