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Markaestro

Markaestro

Official
by markaestro
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Get brand analytics

get_analytics
Read-onlyIdempotent

Retrieve performance analytics for a brand or workspace over a chosen time window, including totals, deltas, channel rollups, engagement, follower trends, top posts, and posting-time insights.

Instructions

Performance over a window for the connection's brand, or on an all-brands connection for the workspace or the one brand named by productId: totals with the prior period for deltas, per-channel rollups, daily series, engagement breakdown, follower trend, top posts, posting-time heatmap, content-type averages, computed insights, and coverage. Covers the whole account: posts published through Markaestro and posts published directly on the platform (discovered from the connected account); coverage.bySource says how many of each. Read this before recommending what, when, or where to post. The window is clamped to the plan's history (the response reports maxDays). Unavailable provider metrics are null, not zero.

Input Schema

NameRequiredDescriptionDefault
tzNoViewer timezone offset in minutes east of UTC; shapes the heatmap only
daysNoPreset window ending today (UTC); default 28
sinceNoExplicit range start, YYYY-MM-DD (UTC); needs until
untilNoExplicit range end, YYYY-MM-DD (UTC), inclusive
sourceNoOnly posts published through Markaestro, or only posts published directly on the platform; omit for the whole account
channelNoRestrict every number to one channel
productIdNoOne brand, on an all-brands connection; omit for the whole workspace. A single-brand connection always reports its own brand.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.4.0
    • changedInput schema / properties / channel / enum
      Previous value: -[
-  "facebook",
-  "instagram",
-  "tiktok",
-  "threads",
-  "pinterest",
-  "linkedin",
-  "x"
-]New value: +[
+  "facebook",
+  "instagram",
+  "tiktok",
+  "threads",
+  "pinterest",
+  "linkedin",
+  "x",
+  "youtube"
+]
  2. First observedv0.3.3

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the extra value here is real: the window is clamped to the plan's history and reported as maxDays, unavailable provider metrics come back as null rather than zero, and data spans both Markaestro-published and platform-discovered posts. It does not describe response shape, but no output schema exists and the sections are enumerated.

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?

Information-dense and front-loaded, with every sentence adding something. However the first sentence is an unusually long dash-chained list, and the fragment 'coverage.' is duplicated awkwardly at the end of sentence one and again in 'coverage.bySource says how many of each'.

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 7-parameter, all-optional analytics tool with no output schema, the definition does the heavy lifting: it enumerates the returned sections, explains the account coverage model, and warns about history clamping and nulls. Missing only explicit deltas against the other analytics siblings.

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 per-parameter descriptions, so the three-baseline applies. The description does add genuine meaning beyond the schema by explaining the productId semantics (omitted = whole workspace; single-brand connections always report their own brand) and by tying source to coverage.bySource.

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 resource and scope: performance for the connection's brand, or workspace/all-brands via productId, with an enumerated list of returned sections (per-channel rollups, daily series, heatmap, insights, coverage). The account-wide vs per-post distinction is implicit in 'Covers the whole account', but no sibling such as get_evergreen_analytics or list_post_analytics is named, so routing still needs inference.

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?

'Read this before recommending what, when, or where to post' gives clear usage context and signals this is the source-of-truth analytics call. No exclusions or explicit alternative-selection rules against the several analytics siblings are given.

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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