SplitLaunch

experiments_set_status

Destructive

Move an experiment through draft, running, paused, and ended states, then return the updated experiment. Only call after the user approves launching, pausing, or ending the experiment.

Input Schema

TableJSON Schema

Name	Required	Description
`status`	Yes	Target lifecycle status. running starts the experiment; paused stops assignment without ending; ended records an end time.
`projectId`	No	Optional project ID. Omit only when the API key is project-scoped or the account has a clear default project.
`experimentId`	Yes	Experiment ID returned by experiments_create or experiments_list.

TDQS

A3.8/5.0

Behavior3/5

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

Annotations already indicate destructive behavior (destructiveHint=true), so the description's addition of returning the updated experiment adds modest context. No contradictions with annotations are present.

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?

Two sentences efficiently cover purpose, return value, and usage condition without redundancy. The description is front-loaded with the main action.

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 state-transition tool with three parameters and no output schema, the description covers the core behavior and precondition. It could expand on allowed transitions or error scenarios, but the schema's enum descriptions partially compensate.

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?

The input schema has 100% coverage with detailed descriptions for all three parameters, including enum semantics for status. The description does not add any parameter-specific information beyond the schema.

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 clearly states the tool's purpose as moving an experiment through lifecycle states (draft, running, paused, ended) and returning the updated experiment. It effectively distinguishes from sibling tools like experiments_update, which handles other modifications, though it does not explicitly differentiate.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear usage guidance: 'Only call after the user approves launching, pausing, or ending the experiment.' This sets a precondition but does not mention when not to use or list alternatives, leaving room for improvement.

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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TDQS

A3.9/5.0

Disambiguation5/5

Each tool targets a distinct resource and action combination (e.g., domains_add, experiments_create, goals_deactivate, reports_experiment_chart). There is no overlap or ambiguity; even the three report tools serve clearly different purposes (totals, time-series, channel breakdown).

Naming Consistency4/5

The vast majority of tools follow a resource_action snake_case pattern (domains_add, experiments_list). A couple deviate (billing_portal, usage_summary) but still place the resource first, making the pattern predictable and easy to parse.

Tool Count5/5

With 23 tools covering projects, domains, experiments, goals, reports, billing, health, and usage, the count is well-scoped for a split-testing platform. Each tool addresses a specific need without ballooning into excessive granularity.

Completeness4/5

The tool surface provides CRUD-like operations for core entities (projects, experiments, goals, domains) and essential report types. Minor gaps exist (no goal update tool, no experiment delete—only archive) but these are reasonable trade-offs for the domain.

Resources

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