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summary_get

Read-onlyIdempotent

Answer "what's the status?" in one call. Returns an activity snapshot for a time window: posts published and failed (plus what's scheduled next), engagement totals summed from each post's latest stats snapshot, comments and reviews received, and DM volume — each broken down per network. Also returns what's still waiting on you: comments and reviews with no reply from you, and DM chats whose newest message is inbound (with how many are about to run out of their 24h messaging window). Prefer this over calling history_list / comments_list / dm_chats_list separately. Two quirks worth knowing: engagement is lifetime-to-date for posts published in the window rather than engagement earned during it, and the awaiting_reply counts describe current state so they don't change with the window (they look back 30 days, returned as window.backlog_from). Post counts are posts — a post sent to three networks counts once — while by_platform counts per-network deliveries. engagement is null when insights are off for the account, dms when DMs are.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoOptional ISO 8601 timestamp (or bare date) ending an explicit range. Defaults to now when only from is given.
fromNoOptional ISO 8601 timestamp (or bare date) starting an explicit range. Overrides window, and the *_previous comparison counts come back null.
windowNoTime window to report on. Defaults to 24h.
profile_group_idNoOptional profile group ID (hashid) to report on a single group. Omit to cover every group the key can reach.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare a safe read-only, idempotent profile, and the description adds substantial behavior beyond that: engagement is lifetime-to-date rather than in-window, awaiting_reply counts are current state looking back 30 days (window.backlog_from), post counts are per-post while by_platform is per-delivery, and engagement/dms are null when insights or DMs are off.

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 purpose and the sibling routing before the caveats, and every sentence carries information. It is a dense unbroken block rather than scannable structure, which slightly hurts readability for its length.

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 no output schema, the description carries the full burden and does so: it enumerates every returned section, the per-network breakdown, the null conditions, and the counting semantics. An agent can interpret the response correctly without guessing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents all four params; baseline is 3. The description adds meaning beyond the schema by tying window semantics to output interpretation (lifetime vs in-window engagement, window.backlog_from) and clarifying null behavior.

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?

States a specific verb and resource ('Returns an activity snapshot for a time window') and enumerates the exact contents: posts published/failed, engagement totals, comments/reviews, DM volume, per network. It is clearly distinguishable from the granular siblings it names.

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 routes the agent: 'Prefer this over calling history_list / comments_list / dm_chats_list separately,' which names the alternatives and the condition that selects this tool. The opening 'Answer "what's the status?" in one call' frames the use case.

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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