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scenario.apply

scenario_apply

Apply a named scenario with schema-valid options to a running React Native or Expo dev build, undoing any active scenario first and returning the scenario's results.

Instructions

Apply a scenario: [name, options?]. Options must fit its schema (scenario.list). Returns what it returns. Applying an active one undoes it first. bridge.restore undoes it.

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": "scenario_apply"
  }
}

Input Schema

NameRequiredDescriptionDefault
argsNoThe tool's arguments, in order (each any JSON value). Leave out for none.
fullNoReturn a result over 32 KB whole instead of a summary of its size and shape.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.2

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description must carry the full behavioral burden, and it does disclose one important trait: applying an already-active scenario undoes it first, and restore reverses it. That is real value, but "Returns what it returns" is a non-statement that leaves the result contract, permissions required, and failure behavior completely undisclosed for a state-changing tool.

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

Conciseness3/5

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

The definition is short and front-loads the payload shape, but it is telegraphic to the point of ambiguity and spends an entire sentence on "Returns what it returns," which contributes nothing. Tightening the undoes/restore relationship into one clear sentence would improve it.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a state-mutating tool with no annotations and no output schema, so the description is the only source of behavioral context. It omits what a scenario is, what state change to expect, how to discover valid names, and what the return value contains, leaving the agent materially under-informed before invoking it.

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 schema already documents both parameters at 100% coverage, so the baseline is 3. The description earns a point by decoding the opaque positional args array into a meaningful [name, options?] ordering and telling the agent options must conform to the scenario's schema, which the schema itself does not convey.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The verb+resource pair ("Apply a scenario") is identifiable and the shape of the call is sketched as [name, options?], but the definition never says what a scenario actually is or what applying one changes. It names scenario.list and bridge.restore, but the reference to bridge.restore rather than the sibling scenario_restore muddies rather than sharpens the distinction.

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 implied guidance: consult scenario.list for the option schema, and use a restore operation to undo. However, it points to bridge.restore instead of the scenario_restore sibling, and gives no clear statement of when to apply versus re-apply versus restore, leaving the agent to infer the workflow.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.