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Google_search_console

by io.github.pipeworx-io

Gsc Search Analytics

gsc_search_analytics
Read-onlyIdempotent

Query Search Console search-performance data: clicks, impressions, CTR, and average position, grouped by dimensions. Use for "top queries/pages last month", organic CTR, ranking trends. siteUrl must be exactly as returned by gsc_list_sites.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endDateYesEnd date, YYYY-MM-DD (inclusive)
siteUrlYesThe property URL exactly as listed by gsc_list_sites (e.g. "https://example.com/" or "sc-domain:example.com")
rowLimitNoMax rows (default 25, max 25000)
startDateYesStart date, YYYY-MM-DD (inclusive). Search Console data lags ~2-3 days.
dimensionsNoGroup results by these dimensions (e.g. ["query"] for top queries, ["page"] for top pages, ["date"] for a time series). Default: none (totals).
searchTypeNoSearch type / data state (default web)
dimensionFilterGroupsNoOptional Search Console dimensionFilterGroups objects to filter rows (e.g. filter query contains "shoes"). Advanced; pass-through to the API.

TDQS

A4/5.0
Behavior3/5

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

Annotations already indicate readOnlyHint, idempotentHint, and non-destructive nature. The description adds modest behavioral context such as data lag (~2-3 days) as noted in the startDate schema description, but does not significantly extend beyond annotations.

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 extremely concise, consisting of two sentences that front-load the core purpose and key usage. Every sentence provides value without 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 absence of an output schema, the description adequately specifies the returned metrics (clicks, impressions, CTR, average position) and grouping. It covers essential information for a moderate-complexity tool with good annotation support.

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

Parameters3/5

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

Schema coverage is 100% with clear descriptions for each parameter, so the description does not need to add much. The description provides high-level purpose but no additional parameter-specific semantics beyond the 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 queries Search Console search-performance data (clicks, impressions, CTR, average position) grouped by dimensions. It provides specific use cases like 'top queries/pages last month' and explicitly links to gsc_list_sites for the required siteUrl format, distinguishing it from siblings.

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 gives clear usage scenarios (top queries/pages, organic CTR, ranking trends) and a prerequisite (siteUrl must be from gsc_list_sites). It does not explicitly mention when not to use this tool, but the context is sufficient for appropriate selection.

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

All Google_search_console toolsInspect
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TDQS

A3.5/5.0
Disambiguation2/5

The set has several overlapping clusters: ask_pipeworx and ask_pipeworx_beta are explicitly identical, multiple polymarket tools (arbitrage, edges, edge_tracker, fill_risk, kalshi_spread) occupy the same prediction-market space, and ai_visibility_check/scan_competitor_ai_presence are near-duplicates. A few tools (memory triad, gsc_* calls) are crisp, but the boundaries between the meta-research tools (ask_pipeworx, deep_research, discover_tools, validate_claim) are not obvious enough to prevent misselection.

Naming Consistency2/5

Naming is a mixed bag: some tools follow snake_case verb_noun (gsc_list_sites, resolve_entity, search_within), others are lowercased concatenations (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded), and several are bare nouns or adjectives (recent_alerts, forget, recall, process). There is no consistent verb style or separator convention across the set.

Tool Count1/5

35 tools is already heavy, but the bigger problem is that only 4 of them (gsc_list_sites, gsc_list_sitemaps, gsc_inspect_url, gsc_search_analytics) relate to the server's stated Google Search Console purpose. The remaining 31 are a sprawling Pipeworx data/prediction-market/memory toolkit, making the count wildly disproportionate to the apparent scope.

Completeness1/5

For a Google Search Console server, the surface is severely incomplete: it can list sites/sitemaps, inspect URLs, and query analytics, but lacks sitemap submission, property add/remove, URL removal/access control, and other core GSC operations. Conversely, the 31 off-domain tools make the domain itself incoherent — an agent cannot tell what this server is actually for.

Resources