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get_insights

Analyze Google Search Console data using 16 pre-built queries to identify trends, opportunities, and performance insights for SEO optimization.

Instructions

Run pre-built analytical queries against synced GSC data. Choose from 16 insight types: summary, top_queries, top_pages, growing_queries, declining_queries, growing_pages, declining_pages, opportunities (queries ranking 5-20 with high impressions — your quick wins), device_breakdown, country_breakdown, page_queries, query_pages, daily_trend, new_queries, lost_queries, branded_split. Requires synced data — run setup first if needed.

Input Schema

TableJSON Schema

Name	Required	Description
`siteUrl`	Yes	GSC property URL.
`insight`	Yes	Insight type to run.
`dateRange`	No	Date range: "7d", "28d", "3m", "6m", "12m", "16m". Default: "28d".
`pageFilter`	No	Filter by URL path (uses LIKE). e.g. "/blog/"
`queryFilter`	No	Filter by query text (uses LIKE).
`device`	No	Filter by device: DESKTOP, MOBILE, TABLET.
`country`	No	Filter by ISO country code.
`brandTerms`	No	Brand terms for branded_split insight.
`limit`	No	Max rows returned. Default: 50.
`minClicks`	No	Minimum clicks threshold.
`minImpressions`	No	Minimum impressions threshold.

Implementation Reference

src/tools/get-insights.ts:8-28 (handler)

Main handler function that executes the get_insights tool. Validates the database exists, routes to the appropriate insight handler based on the insight type parameter, and executes the query with date range calculations.

export function getInsights(params: InsightParams): any {
  const { siteUrl, insight, dateRange = '28d' } = params;
  const dbPath = getDbPath(siteUrl);

  if (!existsSync(dbPath)) {
    throw new Error(`No database found for "${siteUrl}". Run sync_gsc_data first.`);
  }

  const handler = insightHandlers[insight];
  if (!handler) {
    throw new Error(`Unknown insight type: "${insight}". Valid types: ${Object.keys(insightHandlers).join(', ')}`);
  }

  const { current, prior } = getPeriodDates(dateRange);
  const db = new Database(dbPath);
  try {
    return handler(db, params, current, prior);
  } finally {
    db.close();
  }
}

src/server.ts:248-279 (registration)

Tool registration using server.tool() with name 'get_insights'. Defines the input schema using Zod (16 insight types including summary, top_queries, opportunities, etc.) and calls getInsights() handler.

server.tool(
  'get_insights',
  'Run pre-built analytical queries against synced GSC data. Choose from 16 insight types: summary, top_queries, top_pages, growing_queries, declining_queries, growing_pages, declining_pages, opportunities (queries ranking 5-20 with high impressions — your quick wins), device_breakdown, country_breakdown, page_queries, query_pages, daily_trend, new_queries, lost_queries, branded_split. Requires synced data — run setup first if needed.',
  {
    siteUrl: z.string().describe('GSC property URL.'),
    insight: z.enum([
      'summary', 'top_queries', 'top_pages',
      'growing_queries', 'declining_queries',
      'growing_pages', 'declining_pages',
      'opportunities', 'device_breakdown', 'country_breakdown',
      'page_queries', 'query_pages', 'daily_trend',
      'new_queries', 'lost_queries', 'branded_split',
    ]).describe('Insight type to run.'),
    dateRange: z.string().optional().describe('Date range: "7d", "28d", "3m", "6m", "12m", "16m". Default: "28d".'),
    pageFilter: z.string().optional().describe('Filter by URL path (uses LIKE). e.g. "/blog/"'),
    queryFilter: z.string().optional().describe('Filter by query text (uses LIKE).'),
    device: z.string().optional().describe('Filter by device: DESKTOP, MOBILE, TABLET.'),
    country: z.string().optional().describe('Filter by ISO country code.'),
    brandTerms: z.array(z.string()).optional().describe('Brand terms for branded_split insight.'),
    limit: z.number().optional().describe('Max rows returned. Default: 50.'),
    minClicks: z.number().optional().describe('Minimum clicks threshold.'),
    minImpressions: z.number().optional().describe('Minimum impressions threshold.'),
  },
  async (args) => {
    try {
      const result = getInsights(args);
      return { content: [{ type: 'text', text: JSON.stringify(result, null, 2) }] };
    } catch (error) {
      return { content: [{ type: 'text', text: JSON.stringify({ error: (error as Error).message }) }], isError: true };
    }
  }
);

src/types/index.ts:58-70 (schema)

TypeScript interface definition for InsightParams, defining the structure of parameters: siteUrl, insight type, dateRange, filters (pageFilter, queryFilter, device, country), brandTerms, and optional thresholds.

export interface InsightParams {
  siteUrl: string;
  insight: string;
  dateRange?: string;
  pageFilter?: string;
  queryFilter?: string;
  device?: string;
  country?: string;
  brandTerms?: string[];
  limit?: number;
  minClicks?: number;
  minImpressions?: number;
}

src/tools/get-insights.ts:65-560 (handler)

Collection of insight handler implementations (summary, top_queries, growing_queries, opportunities, etc.) that execute SQL queries against the search_analytics database to generate the various insight reports.

const insightHandlers: Record<string, InsightHandler> = {
  summary: (db, params, current, prior) => {
    const f = filterSQL(params);
    const fv = filterValues(params);

    const currentRow = db.queryOne(`
      SELECT
        COALESCE(SUM(clicks), 0) as clicks,
        COALESCE(SUM(impressions), 0) as impressions,
        ROUND(CAST(SUM(clicks) AS REAL) / NULLIF(SUM(impressions), 0), 4) as ctr,
        ROUND(AVG(position), 1) as avg_position
      FROM search_analytics
      WHERE date BETWEEN ? AND ?${f}
    `, [current.startDate, current.endDate, ...fv]);

    const priorRow = db.queryOne(`
      SELECT
        COALESCE(SUM(clicks), 0) as clicks,
        COALESCE(SUM(impressions), 0) as impressions,
        ROUND(CAST(SUM(clicks) AS REAL) / NULLIF(SUM(impressions), 0), 4) as ctr,
        ROUND(AVG(position), 1) as avg_position
      FROM search_analytics
      WHERE date BETWEEN ? AND ?${f}
    `, [prior.startDate, prior.endDate, ...fv]);

    const pctChange = (curr: number, prev: number): number | null =>
      prev === 0 ? null : Math.round(((curr - prev) / prev) * 1000) / 10;

    return {
      insight: 'summary',
      dateRange: { current, prior },
      current: {
        clicks: currentRow.clicks,
        impressions: currentRow.impressions,
        ctr: currentRow.ctr,
        avgPosition: currentRow.avg_position,
      },
      prior: {
        clicks: priorRow.clicks,
        impressions: priorRow.impressions,
        ctr: priorRow.ctr,
        avgPosition: priorRow.avg_position,
      },
      changes: {
        clicks: currentRow.clicks - priorRow.clicks,
        clicksPct: pctChange(currentRow.clicks, priorRow.clicks),
        impressions: currentRow.impressions - priorRow.impressions,
        impressionsPct: pctChange(currentRow.impressions, priorRow.impressions),
        ctr: currentRow.ctr !== null && priorRow.ctr !== null
          ? Math.round((currentRow.ctr - priorRow.ctr) * 10000) / 10000
          : null,
        ctrPct: currentRow.ctr !== null && priorRow.ctr !== null
          ? pctChange(currentRow.ctr, priorRow.ctr)
          : null,
        avgPosition: currentRow.avg_position !== null && priorRow.avg_position !== null
          ? Math.round((currentRow.avg_position - priorRow.avg_position) * 10) / 10
          : null,
        avgPositionPct: currentRow.avg_position !== null && priorRow.avg_position !== null
          ? pctChange(currentRow.avg_position, priorRow.avg_position)
          : null,
      },
    };
  },

  top_queries: (db, params, current, _prior) => {
    const limit = params.limit || 50;
    const f = filterSQL(params);
    const fv = filterValues(params);

    const rows = db.query(`
      SELECT query,
        SUM(clicks) as clicks,
        SUM(impressions) as impressions,
        ROUND(CAST(SUM(clicks) AS REAL) / NULLIF(SUM(impressions), 0), 4) as ctr,
        ROUND(AVG(position), 1) as avg_position
      FROM search_analytics
      WHERE date BETWEEN ? AND ? AND query IS NOT NULL${f}
      GROUP BY query
      ORDER BY clicks DESC
      LIMIT ?
    `, [current.startDate, current.endDate, ...fv, limit]);

    return { insight: 'top_queries', dateRange: current, rows };
  },

  top_pages: (db, params, current, _prior) => {
    const limit = params.limit || 50;
    const f = filterSQL(params);
    const fv = filterValues(params);

    const rows = db.query(`
      SELECT page,
        SUM(clicks) as clicks,
        SUM(impressions) as impressions,
        ROUND(CAST(SUM(clicks) AS REAL) / NULLIF(SUM(impressions), 0), 4) as ctr,
        ROUND(AVG(position), 1) as avg_position
      FROM search_analytics
      WHERE date BETWEEN ? AND ? AND page IS NOT NULL${f}
      GROUP BY page
      ORDER BY clicks DESC
      LIMIT ?
    `, [current.startDate, current.endDate, ...fv, limit]);

    return { insight: 'top_pages', dateRange: current, rows };
  },

  growing_queries: (db, params, current, prior) => {
    const limit = params.limit || 50;
    const f = filterSQL(params);
    const fv = filterValues(params);

    const rows = db.query(`
      SELECT query,
        SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END) as current_clicks,
        SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END) as prior_clicks,
        SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END)
          - SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END) as click_change,
        ROUND(
          (SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END)
           - SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END))
          * 100.0
          / NULLIF(SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END), 0),
          1
        ) as pct_change,
        SUM(CASE WHEN date BETWEEN ? AND ? THEN impressions ELSE 0 END) as current_impressions,
        SUM(CASE WHEN date BETWEEN ? AND ? THEN impressions ELSE 0 END) as prior_impressions
      FROM search_analytics
      WHERE query IS NOT NULL
        AND (date BETWEEN ? AND ? OR date BETWEEN ? AND ?)${f}
      GROUP BY query
      HAVING current_clicks > 0
      ORDER BY click_change DESC
      LIMIT ?
    `, [
      current.startDate, current.endDate,
      prior.startDate, prior.endDate,
      current.startDate, current.endDate,
      prior.startDate, prior.endDate,
      current.startDate, current.endDate,
      prior.startDate, prior.endDate,
      prior.startDate, prior.endDate,
      current.startDate, current.endDate,
      prior.startDate, prior.endDate,
      current.startDate, current.endDate,
      prior.startDate, prior.endDate,
      ...fv,
      limit,
    ]);

    return { insight: 'growing_queries', dateRange: { current, prior }, rows };
  },

  declining_queries: (db, params, current, prior) => {
    const limit = params.limit || 50;
    const f = filterSQL(params);
    const fv = filterValues(params);

    const rows = db.query(`
      SELECT query,
        SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END) as current_clicks,
        SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END) as prior_clicks,
        SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END)
          - SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END) as click_change,
        ROUND(
          (SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END)
           - SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END))
          * 100.0
          / NULLIF(SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END), 0),
          1
        ) as pct_change,
        SUM(CASE WHEN date BETWEEN ? AND ? THEN impressions ELSE 0 END) as current_impressions,
        SUM(CASE WHEN date BETWEEN ? AND ? THEN impressions ELSE 0 END) as prior_impressions
      FROM search_analytics
      WHERE query IS NOT NULL
        AND (date BETWEEN ? AND ? OR date BETWEEN ? AND ?)${f}
      GROUP BY query
      HAVING prior_clicks > 0
      ORDER BY click_change ASC
      LIMIT ?
    `, [
      current.startDate, current.endDate,
      prior.startDate, prior.endDate,
      current.startDate, current.endDate,
      prior.startDate, prior.endDate,
      current.startDate, current.endDate,
      prior.startDate, prior.endDate,
      prior.startDate, prior.endDate,
      current.startDate, current.endDate,
      prior.startDate, prior.endDate,
      current.startDate, current.endDate,
      prior.startDate, prior.endDate,
      ...fv,
      limit,
    ]);

    return { insight: 'declining_queries', dateRange: { current, prior }, rows };
  },

  growing_pages: (db, params, current, prior) => {
    const limit = params.limit || 50;
    const f = filterSQL(params);
    const fv = filterValues(params);

    const rows = db.query(`
      SELECT page,
        SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END) as current_clicks,
        SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END) as prior_clicks,
        SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END)
          - SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END) as click_change,
        ROUND(
          (SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END)
           - SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END))
          * 100.0
          / NULLIF(SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END), 0),
          1
        ) as pct_change
      FROM search_analytics
      WHERE page IS NOT NULL
        AND (date BETWEEN ? AND ? OR date BETWEEN ? AND ?)${f}
      GROUP BY page
      HAVING current_clicks > 0
      ORDER BY click_change DESC
      LIMIT ?
    `, [
      current.startDate, current.endDate,
      prior.startDate, prior.endDate,
      current.startDate, current.endDate,
      prior.startDate, prior.endDate,
      current.startDate, current.endDate,
      prior.startDate, prior.endDate,
      prior.startDate, prior.endDate,
      current.startDate, current.endDate,
      prior.startDate, prior.endDate,
      ...fv,
      limit,
    ]);

    return { insight: 'growing_pages', dateRange: { current, prior }, rows };
  },

  declining_pages: (db, params, current, prior) => {
    const limit = params.limit || 50;
    const f = filterSQL(params);
    const fv = filterValues(params);

    const rows = db.query(`
      SELECT page,
        SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END) as current_clicks,
        SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END) as prior_clicks,
        SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END)
          - SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END) as click_change,
        ROUND(
          (SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END)
           - SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END))
          * 100.0
          / NULLIF(SUM(CASE WHEN date BETWEEN ? AND ? THEN clicks ELSE 0 END), 0),
          1
        ) as pct_change
      FROM search_analytics
      WHERE page IS NOT NULL
        AND (date BETWEEN ? AND ? OR date BETWEEN ? AND ?)${f}
      GROUP BY page
      HAVING prior_clicks > 0
      ORDER BY click_change ASC
      LIMIT ?
    `, [
      current.startDate, current.endDate,
      prior.startDate, prior.endDate,
      current.startDate, current.endDate,
      prior.startDate, prior.endDate,
      current.startDate, current.endDate,
      prior.startDate, prior.endDate,
      prior.startDate, prior.endDate,
      current.startDate, current.endDate,
      prior.startDate, prior.endDate,
      ...fv,
      limit,
    ]);

    return { insight: 'declining_pages', dateRange: { current, prior }, rows };
  },

  opportunities: (db, params, current, _prior) => {
    const limit = params.limit || 50;
    const minImpressions = params.minImpressions || 100;
    const f = filterSQL(params);
    const fv = filterValues(params);

    const rows = db.query(`
      SELECT query,
        SUM(clicks) as clicks,
        SUM(impressions) as impressions,
        ROUND(CAST(SUM(clicks) AS REAL) / NULLIF(SUM(impressions), 0), 4) as ctr,
        ROUND(AVG(position), 1) as avg_position
      FROM search_analytics
      WHERE date BETWEEN ? AND ? AND query IS NOT NULL${f}
      GROUP BY query
      HAVING avg_position BETWEEN 4 AND 20
        AND impressions > ?
      ORDER BY impressions DESC
      LIMIT ?
    `, [current.startDate, current.endDate, ...fv, minImpressions, limit]);

    return { insight: 'opportunities', dateRange: current, rows };
  },

  device_breakdown: (db, params, current, _prior) => {
    const f = filterSQL(params);
    const fv = filterValues(params);

    const rows = db.query(`
      SELECT device,
        SUM(clicks) as clicks,
        SUM(impressions) as impressions,
        ROUND(CAST(SUM(clicks) AS REAL) / NULLIF(SUM(impressions), 0), 4) as ctr,
        ROUND(AVG(position), 1) as avg_position
      FROM search_analytics
      WHERE date BETWEEN ? AND ?${f}
      GROUP BY device
      ORDER BY clicks DESC
    `, [current.startDate, current.endDate, ...fv]);

    return { insight: 'device_breakdown', dateRange: current, rows };
  },

  country_breakdown: (db, params, current, _prior) => {
    const limit = params.limit || 50;
    const f = filterSQL(params);
    const fv = filterValues(params);

    const rows = db.query(`
      SELECT country,
        SUM(clicks) as clicks,
        SUM(impressions) as impressions,
        ROUND(CAST(SUM(clicks) AS REAL) / NULLIF(SUM(impressions), 0), 4) as ctr,
        ROUND(AVG(position), 1) as avg_position
      FROM search_analytics
      WHERE date BETWEEN ? AND ?${f}
      GROUP BY country
      ORDER BY clicks DESC
      LIMIT ?
    `, [current.startDate, current.endDate, ...fv, limit]);

    return { insight: 'country_breakdown', dateRange: current, rows };
  },

  page_queries: (db, params, current, _prior) => {
    const limit = params.limit || 50;
    if (!params.pageFilter) {
      throw new Error('page_queries insight requires the "pageFilter" parameter.');
    }
    const fv: any[] = [];
    let extraFilter = '';
    if (params.device) { extraFilter += ' AND device = ?'; fv.push(params.device); }
    if (params.country) { extraFilter += ' AND country = ?'; fv.push(params.country); }

    const rows = db.query(`
      SELECT query,
        SUM(clicks) as clicks,
        SUM(impressions) as impressions,
        ROUND(CAST(SUM(clicks) AS REAL) / NULLIF(SUM(impressions), 0), 4) as ctr,
        ROUND(AVG(position), 1) as avg_position
      FROM search_analytics
      WHERE page LIKE ? AND date BETWEEN ? AND ? AND query IS NOT NULL${extraFilter}
      GROUP BY query
      ORDER BY clicks DESC
      LIMIT ?
    `, [`%${params.pageFilter}%`, current.startDate, current.endDate, ...fv, limit]);

    return { insight: 'page_queries', dateRange: current, pageFilter: params.pageFilter, rows };
  },

  query_pages: (db, params, current, _prior) => {
    const limit = params.limit || 50;
    if (!params.queryFilter) {
      throw new Error('query_pages insight requires the "queryFilter" parameter.');
    }
    const fv: any[] = [];
    let extraFilter = '';
    if (params.device) { extraFilter += ' AND device = ?'; fv.push(params.device); }
    if (params.country) { extraFilter += ' AND country = ?'; fv.push(params.country); }

    const rows = db.query(`
      SELECT page,
        SUM(clicks) as clicks,
        SUM(impressions) as impressions,
        ROUND(CAST(SUM(clicks) AS REAL) / NULLIF(SUM(impressions), 0), 4) as ctr,
        ROUND(AVG(position), 1) as avg_position
      FROM search_analytics
      WHERE query = ? AND date BETWEEN ? AND ? AND page IS NOT NULL${extraFilter}
      GROUP BY page
      ORDER BY avg_position ASC
      LIMIT ?
    `, [params.queryFilter, current.startDate, current.endDate, ...fv, limit]);

    return { insight: 'query_pages', dateRange: current, queryFilter: params.queryFilter, rows };
  },

  daily_trend: (db, params, current, _prior) => {
    const f = filterSQL(params);
    const fv = filterValues(params);

    const rows = db.query(`
      SELECT date,
        SUM(clicks) as clicks,
        SUM(impressions) as impressions
      FROM search_analytics
      WHERE date BETWEEN ? AND ?${f}
      GROUP BY date
      ORDER BY date ASC
    `, [current.startDate, current.endDate, ...fv]);

    return { insight: 'daily_trend', dateRange: current, rows };
  },

  new_queries: (db, params, current, prior) => {
    const limit = params.limit || 50;
    const f = filterSQL(params);
    const fv = filterValues(params);

    const rows = db.query(`
      SELECT query,
        SUM(clicks) as clicks,
        SUM(impressions) as impressions,
        ROUND(AVG(position), 1) as avg_position
      FROM search_analytics
      WHERE date BETWEEN ? AND ?
        AND query IS NOT NULL${f}
        AND query IN (
          SELECT query FROM search_analytics WHERE date BETWEEN ? AND ? AND query IS NOT NULL
          EXCEPT
          SELECT query FROM search_analytics WHERE date BETWEEN ? AND ? AND query IS NOT NULL
        )
      GROUP BY query
      ORDER BY impressions DESC
      LIMIT ?
    `, [current.startDate, current.endDate, ...fv, current.startDate, current.endDate, prior.startDate, prior.endDate, limit]);

    return { insight: 'new_queries', dateRange: { current, prior }, rows };
  },

  lost_queries: (db, params, current, prior) => {
    const limit = params.limit || 50;
    const f = filterSQL(params);
    const fv = filterValues(params);

    const rows = db.query(`
      SELECT query,
        SUM(clicks) as clicks,
        SUM(impressions) as impressions,
        ROUND(AVG(position), 1) as avg_position
      FROM search_analytics
      WHERE date BETWEEN ? AND ?
        AND query IS NOT NULL${f}
        AND query IN (
          SELECT query FROM search_analytics WHERE date BETWEEN ? AND ? AND query IS NOT NULL
          EXCEPT
          SELECT query FROM search_analytics WHERE date BETWEEN ? AND ? AND query IS NOT NULL
        )
      GROUP BY query
      ORDER BY clicks DESC
      LIMIT ?
    `, [prior.startDate, prior.endDate, ...fv, prior.startDate, prior.endDate, current.startDate, current.endDate, limit]);

    return { insight: 'lost_queries', dateRange: { current, prior }, rows };
  },

  branded_split: (db, params, current, _prior) => {
    if (!params.brandTerms || params.brandTerms.length === 0) {
      throw new Error('branded_split insight requires the "brandTerms" parameter (array of brand terms).');
    }

    const f = filterSQL(params);
    const fv = filterValues(params);

    // Build CASE expression for brand matching
    const brandConditions = params.brandTerms
      .map(() => 'LOWER(query) LIKE ?')
      .join(' OR ');
    const brandValues = params.brandTerms.map((t) => `%${t.toLowerCase()}%`);

    const rows = db.query(`
      SELECT
        CASE WHEN (${brandConditions}) THEN 'branded' ELSE 'non-branded' END as segment,
        SUM(clicks) as clicks,
        SUM(impressions) as impressions,
        ROUND(CAST(SUM(clicks) AS REAL) / NULLIF(SUM(impressions), 0), 4) as ctr,
        ROUND(AVG(position), 1) as avg_position
      FROM search_analytics
      WHERE date BETWEEN ? AND ? AND query IS NOT NULL${f}
      GROUP BY segment
    `, [...brandValues, current.startDate, current.endDate, ...fv]);

    return { insight: 'branded_split', dateRange: current, brandTerms: params.brandTerms, rows };
  },
};

Tool Definition Quality

A4.1/5.0

Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the prerequisite (synced data) which is crucial context, but doesn't describe other important behaviors: whether this is a read-only operation, what the output format looks like (tabular data? JSON structure?), whether there are rate limits, or what happens with large result sets. The description adds some value but leaves significant behavioral aspects unspecified.

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 efficiently structured: it starts with the core purpose, immediately lists all insight types (essential information), provides helpful parenthetical explanations for key insights like 'opportunities', and ends with the critical prerequisite. Every sentence earns its place, and the information is front-loaded with the most important details first.

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

Completeness3/5

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

Given the tool's complexity (11 parameters, no output schema, no annotations), the description is incomplete. While it covers the purpose, insight types, and prerequisite well, it doesn't address the output format, result limitations, or behavioral characteristics needed for a tool with this many parameters and analytical complexity. The agent would need to guess about the return structure and operational constraints.

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?

The schema description coverage is 100%, so the schema already documents all 11 parameters thoroughly. The description adds minimal parameter semantics beyond the schema - it lists the 16 insight types (which the enum already contains) and briefly explains the 'opportunities' insight. However, it doesn't provide additional context about parameter interactions or usage patterns that would help the agent beyond what's in the schema descriptions.

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 purpose: 'Run pre-built analytical queries against synced GSC data.' It specifies the verb ('run'), resource ('pre-built analytical queries'), and target data ('synced GSC data'). It also lists all 16 insight types, providing specific differentiation from sibling tools like 'query_gsc_data' (which likely runs custom queries) and 'get_overview' (which might provide general metrics).

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 provides explicit usage guidance: 'Requires synced data — run setup first if needed.' This tells the agent when NOT to use this tool (if data isn't synced) and what alternative to use first ('setup'). It also implies this tool is for analytical insights rather than raw data queries, distinguishing it from siblings like 'query_gsc_data'.

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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