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List automations

sprkly_list_automations
Read-only

Every Instagram automation on this account that is not archived. Each row has its name, its state (On, Paused or Draft), the Instagram account it runs on, what starts it, and how many DMs and public replies it has sent. ends_at is when it switches itself off (null = no end), and ended is true once that time has passed. campaign is its campaign label, or null. One automation on several accounts shows one row per account, all with the same group_id.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "sprkly_list_automations"
  }
}

Input 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 read-only, closed-world, non-destructive behavior, so the lower bar applies. Beyond that, the description adds real context: archived automations are excluded, multi-account automations produce one row per account, and rows share a group_id. That row-granularity and grouping rule is exactly the kind of behavior an agent cannot infer from 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?

Scope is front-loaded in sentence one, then field semantics follow in a compact run. Every sentence carries information about the returned rows. It is slightly dense and could be broken into a short bulleted field list for faster scanning, which keeps it off a 5.

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?

There is no output schema, so the description must explain return values, and it does so thoroughly: fields, state enum values (On, Paused, Draft), ends_at null semantics, the ended flag, campaign nullability, and group_id. Ordering and pagination behavior are not addressed, which is the only meaningful gap for a list tool.

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 zero parameters and 100% coverage, the baseline is 4. The description correctly adds no parameter guidance and instead spends its words on what comes back, which is the right allocation for a no-arg tool.

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 first sentence gives a specific verb (list) and resource (Instagram automations) with a clear scope qualifier: not archived, on this account. That scope qualifier alone separates it from the automation-template and insights siblings. It stops short of explicitly naming a sibling, so a 4 rather than a 5.

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 implied by the listing framing and the archived-exclusion clause (which hints archive_automation exists elsewhere), but there is no explicit when-to-use or when-to-prefer instruction. Nothing tells the agent whether to call this before get_automation_insights, get_automation_usage, or pause/resume operations.

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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