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sprkly-mcp

Get automation usage

sprkly_get_automation_usage
Read-only

For each Instagram account: how many people automations have messaged this month, the plan's monthly limit for that account, and when the count resets. ready is false when Instagram has not given the messaging permission yet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered; the description adds real behavioral value on top by defining the `ready` flag and its cause (Instagram has not yet granted messaging permission) and by scoping the counts to a monthly window with a stated reset. It stops short of describing throttling, auth requirements, or partial-failure behavior across accounts.

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 sentences with no filler; the core payload (what is counted, the limit, the reset) leads, and the `ready` caveat follows. The first sentence is dense but each clause carries distinct information, so nothing is wasted.

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 zero-parameter, read-only tool with no output schema, the description does the heavy lifting of describing the return shape (count, limit, reset, ready) and is therefore close to complete. Minor gaps remain around error/empty states (e.g. accounts with no automations) and whether results are paginated, but nothing essential to invoking it is missing.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate and the baseline of 4 applies. No parameter meaning is lost.

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 a specific resource (automation usage) and enumerates exactly what is returned: per-Instagram-account message counts, the plan's monthly limit, and the reset date. This clearly separates it from sprkly_list_automations (which lists automations) and sprkly_get_billing_summary, though it never explicitly contrasts with those quota-adjacent siblings.

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?

There is no explicit 'use this when...' statement or named alternative. The use case (checking messaging quota headroom before enabling an automation) is inferable from the enumerated return values, but the agent has to derive it — implied usage rather than stated 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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