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markaestro

Markaestro

Official

Refresh analytics from the platforms

refresh_analytics

Pull live social metrics now instead of waiting for the next scheduled poll: update post and follower counts for a chosen window, channel, or brand, and see how many posts updated or remain.

Instructions

Pull live metrics from the platforms now instead of waiting for the next scheduled poll: posts in the window (optionally one channel, or one brand on an all-brands connection) and today's follower counts. The answer says how many posts were updated and how many remain, since a large window may take more than one refresh. Limited to a few calls a minute.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoWindow ending now; default 28
channelNo
productIdNoOne brand, on an all-brands connection

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.3

TDQS

A3.8/5.0
Behavior4/5

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

Adds substantial behavior beyond annotations: it discloses the rate limit ('a few calls a minute'), the non-atomic nature of the operation ('how many posts were updated and how many remain... a large window may take more than one refresh'), and the exact scope of what gets refreshed. This meaningfully supplements the readOnlyHint=false / idempotentHint=false annotations.

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?

Three dense sentences, front-loaded with the core action and its contrast to scheduled polling, followed by response behavior and the rate limit. Every sentence carries information; no obvious 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?

Despite no output schema, the description explains the return payload (counts of updated and remaining posts) and the partial-completion caveat, and covers the parameter interactions and rate limit. Sufficient for an agent to invoke it correctly.

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?

With 67% schema coverage, the schema documents days and productId but leaves channel's enum undocumented. The description compensates by explaining 'optionally one channel, or one brand on an all-brands connection', clarifying how the two optional filters interact and what 'window' means for days.

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+resource ('Pull live metrics from the platforms') and contrasts it with the scheduled poll, so the agent understands it forces an on-demand refresh rather than reading cached data. It does not name sibling tools like get_analytics, so differentiation is only implicit.

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?

'Now instead of waiting for the next scheduled poll' implies when to reach for it, and the rate-limit note constrains usage. However, it never names an alternative (e.g., get_analytics) or states when-not-to-use, so the agent must infer the boundary.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.