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stop_emr_application

Stop an EMR Serverless application by first canceling any running jobs, then halting the application. Provides step-by-step execution reports.

Instructions

Stop an EMR Serverless application. If jobs are running, cancels them first.

Smart flow:

  1. Tries to stop the application directly.

  2. If it fails because jobs are still running — automatically finds and cancels ALL running/pending jobs, then retries the stop.

  3. Reports every step taken so the user knows exactly what happened.

Use force=True to skip the initial stop attempt and go straight to cancelling all jobs first (useful when you know jobs are running).

Args: application_id: The EMR Serverless application ID. force: If True, cancel all running jobs first without trying to stop. env: Target environment — 'dev', 'uat', 'test', or 'prod'. IMPORTANT: Do NOT guess or default. Ask the user which environment if not specified.

Returns a step-by-step report of what was done.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
application_idYes
forceNo
envNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure and does so effectively. It explains the multi-step flow (stop attempt → job cancellation → retry), discloses that it cancels ALL running/pending jobs, specifies that it reports every step taken, and explains the force parameter's bypass behavior. The only minor gap is lack of explicit mention about permissions or rate limits, but overall it provides rich behavioral context.

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?

The description is well-structured with clear sections (purpose, smart flow, parameter guidance, return value) and every sentence earns its place. It's appropriately sized for a complex tool with multi-step behavior. The only minor improvement would be slightly tighter formatting, but it's highly efficient overall.

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?

Given this is a complex mutation tool with no annotations, 3 parameters, and an output schema, the description provides excellent completeness. It explains the multi-step behavior, parameter semantics, usage guidelines, and explicitly states what the tool returns ('step-by-step report'). The presence of an output schema means the description doesn't need to detail return format, making this description complete for its context.

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

Parameters5/5

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

With 0% schema description coverage, the description fully compensates by providing detailed semantic explanations for all three parameters. It explains what 'application_id' represents, when and why to use 'force=True', and provides critical guidance about the 'env' parameter (valid values and the requirement to ask users rather than guessing defaults). This adds substantial value beyond the bare schema.

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?

The description starts with a clear, specific verb+resource statement: 'Stop an EMR Serverless application.' It distinguishes from siblings like 'cancel_job_run' and 'delete_emr_application' by focusing on stopping (not deleting) applications and handling job cancellation as part of the process. The purpose is unambiguous and well-differentiated.

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?

The description provides explicit guidance on when to use this tool vs alternatives through the 'Smart flow' section and the 'force' parameter explanation. It tells users to use 'force=True' when they know jobs are running, and importantly specifies when NOT to guess defaults for the 'env' parameter, requiring explicit user input. This gives clear operational context.

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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