StreamClipping AI

Publishing analytics

get_analytics

Read-only

Views, likes and top posts over a period, per platform. Only covers posts published from StreamClipping AI.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`creator`	No	Agency creator to scope to, by name or id (see the creator profiles of the account). 'default' targets the default profile, the one without a named creator. Omit to cover all creators of the organization.
`periodDays`	No	Analysis window, in days.

Output Schema

TableJSON Schema

Name	Required	Description
`note`	Yes	Reading note, in particular when no data is available.
`topPosts`	Yes
`byPlatform`	Yes
`periodDays`	Yes
`totalLikes`	Yes
`totalViews`	Yes
`publishedPosts`	Yes
`avgViewsPerPost`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 16, 2026

addedInput schema / properties / creator

Added value: +{
+  "description": "Agency creator to scope to, by name or id (see the creator profiles of the account). 'default' targets the default profile, the one without a named creator. Omit to cover all creators of the organization.",
+  "maxLength": 100,
+  "minLength": 1,
+  "type": "string"
+}

First observedOct 9, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already establish readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds a genuinely useful behavioral constraint beyond that: results only cover posts published through StreamClipping AI, which tells the agent why coverage may be incomplete. Return format and aggregation semantics are left to the output schema.

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?

Two short sentences, zero filler. The positive statement of what is returned is front-loaded and the coverage caveat follows immediately, so nothing has to be scanned for.

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 an output schema present, return values need no explanation, and annotations carry the safety profile. The description supplies the one thing structured fields can't: the StreamClipping-AI-only data scope. Only the absence of guidance on the 'per platform' breakdown versus parameters is a residual gap.

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%, with creator and periodDays both fully documented in the schema, so the baseline is 3. The description's 'over a period, per platform' loosely gestures at periodDays but says nothing about creator scoping or the 'default' sentinel, adding little 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?

The description names the concrete outputs (views, likes, top posts), the aggregation window and the breakdown dimension (per platform), so an agent can tell it is the reporting tool rather than a listing or mutation tool. It is clear but never states a verb or explicitly contrasts itself with siblings such as get_account or list_clips.

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?

Usage is only implied: reading performance metrics. There is no statement of when to reach for this versus the sibling listing tools, nor any prerequisite (e.g., needing published posts to exist). The scope caveat 'only covers posts published from StreamClipping AI' hints at when results will be empty but is framed as data scope, not usage guidance.

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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