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AdaptlyPost

by com.adaptlypost
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Get Analytics Timeseries

get_analytics_timeseries
Read-only

Views, likes, comments, shares, followers, posts published and engagement rate bucketed by day (default), week or month across the window, for trend questions such as "how are views moving" or "when did followers jump". Returns { points } with one { date, ...metrics } per bucket; followers is the latest count at the end of the bucket, the other counters sum posts published inside it, and a metric no selected platform reports is null. Use get_analytics_overview for totals and list_post_analytics to see which posts drove a spike.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesEnd of the reporting window (ISO 8601). Must not be earlier than from
fromYesStart of the reporting window as an ISO 8601 date or instant (e.g. "2026-08-01"). Metrics cover posts published between from and to; the comparison window is the same length immediately before from
platformsNoRestrict to these platforms; omit for every platform with analytics. X (TWITTER) and MASTODON have no analytics and are ignored; LinkedIn analytics are pending platform approval and return no data yet
granularityNoDAILY (default), WEEKLY, or MONTHLY buckets
workspaceIdNoWorkspace to act in: an id from list_workspaces. Omit to act in the workspace list_workspaces marks current. Use the same workspaceId for every call about the same workspace, since ids from one workspace (accounts, posts, uploads) do not exist in another

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoAn object with points: one { date, views, likes, comments, shares, followers, postsCount, engagementRate } per bucket, in date order.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
    • removedOutput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
  2. Changed1 schema field changed
    • changedInput schema / properties / workspaceId / description
      Previous value: -"Workspace to act in: an id from list_workspaces. Omit to use the default workspace. Use the same workspaceId for every call about the same workspace, since ids from one workspace (accounts, posts, uploads) do not exist in another"New value: +"Workspace to act in: an id from list_workspaces. Omit to act in the workspace list_workspaces marks current. Use the same workspaceId for every call about the same workspace, since ids from one workspace (accounts, posts, uploads) do not exist in another"
  3. Changed1 schema field changed
    • addedInput schema / properties / workspaceId
      Added value: +{
+  "description": "Workspace to act in: an id from list_workspaces. Omit to use the default workspace. Use the same workspaceId for every call about the same workspace, since ids from one workspace (accounts, posts, uploads) do not exist in another",
+  "type": "string"
+}
  4. Changed2 schema fields changed
    • changedInput schema / properties / platforms / description
      Previous value: -"Restrict to these platforms; omit for every platform with analytics. X (TWITTER) has no analytics and is ignored; LinkedIn analytics are pending platform approval and return no data yet"New value: +"Restrict to these platforms; omit for every platform with analytics. X (TWITTER) and MASTODON have no analytics and are ignored; LinkedIn analytics are pending platform approval and return no data yet"
    • changedInput schema / properties / platforms / items / enum
      Previous value: -[
-  "LINKEDIN",
-  "YOUTUBE",
-  "INSTAGRAM",
-  "FACEBOOK",
-  "TIKTOK",
-  "PINTEREST",
-  "THREADS",
-  "BLUESKY",
-  "TWITTER"
-]New value: +[
+  "LINKEDIN",
+  "YOUTUBE",
+  "INSTAGRAM",
+  "FACEBOOK",
+  "TIKTOK",
+  "PINTEREST",
+  "THREADS",
+  "BLUESKY",
+  "TWITTER",
+  "MASTODON"
+]
  5. Added

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already cover the safety profile (readOnlyHint true, destructiveHint false, openWorldHint false), so the bar is lower. The description adds valuable behavioral detail beyond annotations: the return shape ({ points } with one { date, ...metrics } per bucket), the aggregation semantics (followers is the latest count at bucket end, other counters sum posts published inside it), and null handling for metrics not reported by a selected platform.

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 front-loaded with what the tool does, then returns semantics, then alternatives. Every sentence earns its place: the first defines the tool, the second describes the output and aggregation rules, the third routes to siblings. No filler.

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?

With an output schema present, the description need not explain return values, but it does so succinctly where it matters for interpretation. Combined with full schema coverage and clear annotations, an agent has everything needed to invoke the tool correctly: purpose, alternatives, return shape, and aggregation rules.

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 the schema already documents all five parameters in detail, including platform restrictions, granularity default, and workspaceId usage. The description adds little parameter-specific meaning beyond what the schema provides; it reinforces platform behavior indirectly through the null-returning metric note, but that is not parameter guidance per se.

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 names the specific metrics (views, likes, comments, shares, followers, posts published, engagement rate) and the bucketing dimension (day, week, month), so the agent knows exactly what the tool produces. It also distinguishes the tool from siblings by naming get_analytics_overview for totals and list_post_analytics for post-level drill-down.

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?

Explicitly states the use case (trend questions such as 'how are views moving' or 'when did followers jump') and names the two alternatives with their respective roles. This gives the agent a clear routing decision without needing to infer from schemas.

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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