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Suganthan-Mohanadasan

Google Search Console MCP Server

generate_report

Generate a markdown performance report covering site snapshot, alerts, quick wins, traffic drops, content decay, and recommendations. Save to disk for weekly reviews.

Instructions

Generate a comprehensive markdown performance report. Covers site snapshot, alerts, quick wins, traffic drops, content decay, and recommendations. Saves to disk for weekly reviews or scheduled reporting. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoNumber of days to analyse
output_pathNoFile path to save the report (default: ./gsc-report-{date}.md)
include_sectionsNoSections: snapshot, alerts, quick_wins, traffic_drops, content_decay, recommendations
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 delivers extensively. It includes critical rules like basing analysis only on returned data, citing exact numbers, avoiding speculation unless supported, explicitly saying when data is insufficient, and requiring presentation as interactive visualizations with specific formatting. This goes far beyond a basic summary.

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

Conciseness4/5

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

The description is relatively long, but it is well-structured with clear sections for the main action, analysis constraints (IMPORTANT), and presentation requirements (PRESENTATION). Each sentence earns its place, though some of the presentation details could be considered slightly verbose. It is arguably necessary for such a complex tool.

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?

Given the complexity of the tool (combining multiple report sections), the absence of an output schema, and no annotations, the description provides thorough context. It explains the report's contents, data analysis rules, handling of insufficient data, presentation format, and file-saving behavior. The only minor gap is that the return value is not explicitly stated, but the overall completeness is high.

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?

All three parameters (days, output_path, include_sections) are already fully described in the schema with 100% coverage. The tool description adds no additional semantic details about parameter usage or interdependencies, so the baseline score of 3 is appropriate.

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's function: 'Generate a comprehensive markdown performance report.' It lists the specific sections covered (snapshot, alerts, quick wins, traffic drops, content decay, recommendations), which distinguishes it from sibling tools that focus on individual analyses.

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 appropriate usage contexts such as 'weekly reviews or scheduled reporting,' giving a clear sense of when to use the tool. However, it does not explicitly contrast with alternative sibling tools or state when not to use it, so it falls short of a 5.

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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