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roasr_signals

Get Google, Meta, and Yandex ad signals by kind - search terms, quality scores, impression share, auction insights - with per-account snapshots.

Instructions

Rich signals for a date window by kind: Google search terms, keyword quality score, impression share, auction insights, conversion actions by category, asset performance, landing pages, shopping, video funnel, bidding, asset groups; Meta — ad quality rankings. Per-account latest snapshot inside the window (payloads of different accounts are not aggregated); the response is capped by limit (default 50) — this is intel the plain metrics tools do not have.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYessignal kind, required: google_search_terms | google_keywords_qs | google_impression_share | google_auction_insights | google_conversion_actions | google_asset_performance | google_landing_pages | google_shopping | google_video_funnel | google_bidding | google_asset_groups | meta_ad_quality | yandex_search_queries | yandex_keywords | yandex_ad_moderation | yandex_bidding
limitNohow many rows to return (1–200, default 50)
sinceNowindow start, YYYY-MM-DD (use with until; takes priority over sinceDays)
untilNowindow end, YYYY-MM-DD (defaults to today)
clientIdNoclient UUID (optional)
accountIdNoad account UUID (optional)
sinceDaysNowindow in days back from today (1–365, default 30)
Behavior4/5

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

With no annotations provided, the description carries the full burden and does disclose several key behaviors: 'Per-account latest snapshot inside the window (payloads of different accounts are not aggregated)' and 'response is capped by limit (default 50)'. This goes beyond a simple 'get data' claim and gives the agent useful operational context, though it doesn't detail permissions or per-kind payload schemas.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact yet information-dense. It front-loads the core purpose, uses a list to convey many signal kinds without fluff, and includes important behavioral caveats in a single dash-separated clause. Every sentence earns its place with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (16 enum kinds, 7 parameters, no output schema), the description covers the essential operational semantics: what the tool returns, how it scopes data (date window, per-account snapshot), and the response cap. It doesn't describe the exact output structure for each kind, but the kind names are self-explanatory and the schema covers parameters, making the description adequate for selection.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds value by explaining that 'kind' groups the signal categories, that the window is per-account snapshot with non-aggregated payloads, and that 'limit' caps the response. These are not explicit in the schema's property descriptions and help the agent understand parameter roles.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool provides 'rich signals for a date window by kind' and enumerates the specific signal categories (Google search terms, auction insights, etc.). It explicitly distinguishes itself from siblings by noting 'this is intel the plain metrics tools do not have', which helps an agent differentiate it from the metrics-summary/breakdown tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use when non-metric diagnostic signals are needed ('intel the plain metrics tools do not have') and when a per-account latest snapshot is desired. It does not name specific alternative tools or state explicit when-not-to-use scenarios, but the context is clear enough for an agent to decide.

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

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