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Get analytics summary

get_analytics_summary
Read-onlyIdempotent

Returns summary counts for a period. Covers matched and relevant mentions, unique posts and people, sentiment, buying intent, questions, reach and triage. Reach sums followers where known. Triage gives open, ignored and done counts, mentions waiting over 24h, handled rate and median time to done. Set the period with range (7d, 30d, 90d or 365d, ending today) or from and to (YYYY-MM-DD). keywordIds and platforms take lists. timezone (IANA, default UTC) sets day boundaries. compare=true adds the prior period as previous. Dates are publish dates.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_analytics_summary"
  }
}

Input Schema

NameRequiredDescriptionDefault
toNoEnd date in `timezone`, as YYYY-MM-DD, included. Defaults to today.
fromNoStart date in `timezone`, as YYYY-MM-DD. That day is included.
rangeNoA preset period up to today, 30d by default. Ignored when you send from or to.
compareNotrue adds the equally long period just before as `previous`.
timezoneNoThe IANA time zone used to split days, such as America/New_York. Defaults to UTC. The zone's offset at the end of the period is used for the whole period.
platformsNoKeeps these platforms only. Repeat the parameter or separate values with commas. Leave it out for all platforms.
keywordIdsNoKeeps these keyword ids only. Repeat the parameter or separate values with commas. Leave it out for all keywords.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / platforms / items / enum
      Previous value: -[
      -  "bluesky",
      -  "hackernews",
      -  "github",
      -  "stackoverflow",
      -  "devto",
      -  "reddit",
      -  "x",
      -  "youtube",
      -  "news",
      -  "linkedin",
      -  "tiktok",
      -  "instagram",
      -  "appstore",
      -  "googleplay",
      -  "trustpilot",
      -  "googlemaps"
      -]New value: +[
      +  "bluesky",
      +  "hackernews",
      +  "github",
      +  "stackoverflow",
      +  "devto",
      +  "reddit",
      +  "x",
      +  "youtube",
      +  "news",
      +  "linkedin",
      +  "tiktok",
      +  "instagram",
      +  "appstore",
      +  "googleplay",
      +  "trustpilot",
      +  "googlemaps",
      +  "rss"
      +]
  2. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already establish readOnlyHint, idempotentHint and destructiveHint=false, lowering the bar. The description still adds real behavioral detail beyond them: 'Reach sums followers where known', precise triage definitions ('open, ignored and done counts, mentions waiting over 24h, handled rate and median time to done'), timezone offset being applied across the whole period, and that dates are publish dates rather than ingest dates.

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?

Front-loaded with the core purpose, then grouped by metric family before moving to period and filter mechanics. It is dense and reads as a long run of short clauses, but nearly every clause carries distinct information (metric definitions, timezone semantics, `previous` key) rather than padding.

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?

With no output schema, the description carries the burden of describing returns, and it does so reasonably well by naming the count families, the reach follower rule, the triage composition and the `previous` comparison block. Minor gaps remain: no pagination/size expectations and no indication of what a zero-data period returns, but nothing essential to invoking it is missing.

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 description coverage is 100%, so every parameter is already documented, setting the baseline at 3. The description restates the range/from-to precedence and list handling that the schema already covers, adding mainly the output-side detail that compare=true is exposed as `previous`; that is helpful but it is not parameter-level clarification beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Returns summary counts for a period') and enumerates the metric families covered (mentions, sentiment, buying intent, reach, triage). This lets an agent distinguish it from get_share_of_voice and get_mention_stats, but it never explicitly contrasts itself with the closest siblings get_analytics_breakdown and get_analytics_series, so the reader must infer the summary/breakdown/series split from names alone.

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

Usage Guidelines3/5

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

The description gives practical framing on how to set the period and the default (range 30d, ending today), which implies a time-bounded aggregate query. However it offers no explicit when-to-use guidance against get_analytics_breakdown or get_analytics_series, and no exclusions, so usage is inferred rather than stated.

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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