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Heista

by co.heista

Fleet — Search Console Live Query

fleet_gsc_query
Read-onlyIdempotent

LIVE Google Search Analytics query — group by any dimensions (date, page, query, country, device, searchAppearance; up to 3) with page/query filters over up to 16 months of history. Richer than the snapshot tools: use this for ad-hoc analysis. NOTE: including the "query" dimension omits anonymized rare queries — use ["date"] or ["page"] for complete totals on low-traffic sites. Hard cap 100 rows. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateNoISO date. Default: 3 days ago (GSC lags ~2-3 days).
row_limitNoMax rows (default 25, hard cap 100).
dimensionsYesGroup-by dimensions, up to 3 (e.g. ["query"], ["page","query"], ["date"]). NOTE: including "query" omits anonymized/rare queries — totals with ["date"] or ["page"] are more complete on low-traffic sites.
start_dateNoISO date (YYYY-MM-DD). Default: 28 days ago. GSC holds ~16 months of history.
page_containsNoFilter: page URL contains this string (e.g. "/decode").
query_containsNoFilter: search query contains this string.

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already provide readOnlyHint and idempotentHint; the description adds behavioral details like 'LIVE', hard cap of 100 rows, and data lag (~2-3 days), enhancing transparency.

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?

Two clear sentences plus a NOTE, efficient with no wasted words; key information is front-loaded.

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

Completeness5/5

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

The description covers purpose, usage, limitations, and important caveats (e.g., query dimension omission, data lag, history length), making it complete for the tool's complexity.

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 covers 100% of parameters with descriptions; the description adds value through contextual notes (e.g., query dimension caveat) but does not significantly extend beyond schema.

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 it's a LIVE Google Search Analytics query that groups by up to 3 dimensions with filters over 16 months, distinguishing it from snapshot tools.

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

Usage Guidelines5/5

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

Explicitly advises when to use it ('ad-hoc analysis') versus snapshot tools, and includes a specific NOTE about when to avoid certain dimensions for complete totals.

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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TDQS

A3.7/5.0
Disambiguation4/5

Despite the high tool count, most tools have distinct purposes with thorough descriptions that specify when to use each. Some overlap exists among creative direction tools (call_creative_worlds vs chat_with_creative_worlds), but the descriptions clarify usage patterns.

Naming Consistency3/5

Naming conventions are inconsistent overall: some follow verb_noun (create_powersource_url, decode_ad), others use noun_verb or compound names (adformula_intelligence, fleet_analytics_overview). However, subgroups like dispatch_* and list_*_presets maintain internal consistency.

Tool Count2/5

112 tools is far beyond the typical 3-15 range for well-scoped servers. While the server covers a broad domain, the sheer number likely overwhelms agents and suggests insufficient consolidation of related operations.

Completeness4/5

The tool set covers core creative intelligence workflows: brand analysis, ad decoding, script generation, creative direction, and research. Minor gaps exist (e.g., no social media publishing tools), but the main use cases are well-supported.

Resources