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Destroy Experiment

destroy_experiment

Terminate an experiment's sandbox and free its resources, returning a final report of changes to summarize what happened.

Instructions

Destroy a sandbox and everything in it, returning a final report.

USE THIS as soon as an experiment has told you what you needed. Always call it -- a sandbox left running keeps consuming the developer's CPU and memory.

IDEMPOTENT: calling it on an already-destroyed experiment is safe and returns the stored report rather than an error.

RETURNS the final report, including what changed inside the sandbox, so you can summarise the experiment after it is gone.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
experiment_idYesThe experiment to destroy.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
reportNo
statusYes
experiment_idYes
jobs_cancelledNo
snapshot_removedNo
already_destroyedNo
container_removedNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

No annotations are provided, so the description carries the full behavioral burden and meets it: it discloses the destructive nature, idempotency ('calling it on an already-destroyed experiment is safe and returns the stored report rather than an error'), and the return contract ('what changed inside the sandbox'). This is exactly the disclosure an agent needs for a destructive call.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core action and organized into clearly labeled sections (usage directive, idempotency, returns). Every sentence earns its place by adding a distinct piece of information — there is no filler, repetition, or vague phrasing.

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?

For a destructive single-parameter tool with no annotations, the description is complete: it states the action, when to call it, the cost of not calling it, the idempotent re-call behavior, and the contents of the return. An output schema exists, so the return structure itself is already covered structurally.

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

Parameters3/5

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

Schema description coverage is 100% — the sole parameter experiment_id is already documented as 'The experiment to destroy.' The description adds no parameter-specific detail beyond the schema, so the baseline of 3 applies.

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 states a specific verb and resource — 'Destroy a sandbox and everything in it' — and adds the outcome ('returning a final report'). This clearly differentiates it from siblings like get_experiment (read-only), execute_experiment (run), and cancel_job (cancel a job, not destroy the sandbox).

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 gives explicit when-to-use guidance: 'USE THIS as soon as an experiment has told you what you needed. Always call it.' It also supplies the rationale (a sandbox left running consumes CPU and memory) and implicitly tells the agent not to call it prematurely — collect what you need first, then destroy.

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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