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by io.github.deleteweb
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get_gsc_performance

Performance Search Console del progetto aggregata per query o pagina (click, impression, CTR, posizione media), con totali del periodo. I dati sono pre-aggregati in finestre di 7, 28 o 90 giorni: un valore diverso viene arrotondato per eccesso e la risposta riporta in days la finestra EFFETTIVA (days_requested = quella chiesta). Qui non c'è storico giorno per giorno: per datare un calo usa get_gsc_daily.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "project_id": "<project_id>"
    },
    "name": "get_gsc_performance"
  }
}

Input Schema

NameRequiredDescriptionDefault
daysNo
limitNo
dimensionNo
project_idYesID progetto (da list_projects)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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 so well: it reveals pre-aggregation into 7/28/90-day windows, the rounding-up behavior for other values, the effective vs requested window fields (`days` vs `days_requested`), and the absence of daily granularity. No annotation contradiction exists.

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?

Three dense sentences: purpose/metrics first, then aggregation semantics, then the explicit alternative. Every sentence earns its place and the most decision-relevant contrast is front-loaded.

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?

For a 4-parameter tool with no annotations and no output schema, the description covers purpose, metrics, dimensions, and the unusual window rounding behavior. The main gap is the lack of any explanation for `limit` and a fuller picture of the response shape, though the named fields and metrics make it mostly adequate.

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 low (25%), so the description meaningfully compensates by explaining the `days` window behavior and the `dimension` options ('per query o pagina'). However, the `limit` parameter and the exact relationship between `days_requested` and the query parameter are not fully elaborated, leaving a small but real semantic gap.

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 states exactly what the tool does: it returns Search Console performance aggregated by query or page, with period totals for clicks, impressions, CTR, and average position. It also explicitly contrasts itself with get_gsc_daily, so the agent can distinguish it from the closest sibling.

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?

The description explicitly says this tool provides no day-by-day history and instructs agents to use get_gsc_daily when dating a decline. This is a clear when-to-use/when-not-to-use statement with a named alternative.

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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