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orchestrator.run_android_validation_loop

Automate Android app validation: build, install, run Appium tests, verify results, collect evidence, and iterate until goals are met.

Instructions

[approval required][device mutation][risk:dangerous] Run build -> install -> Appium scripted test -> verification -> evidence -> loop record for Android.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalYes
kindNo
serialNo
apkPathNo
avdNameNo
runLintNo
apiChecksNo
appiumStepsNo
packageNameNo
clearAppDataNo
runUnitTestsNo
buildDebugApkNo
expectedTextsNo
collectEvidenceNo
iterationOffsetNo
maxTestIterationsNo
appiumCapabilitiesNo
flowReplayTestNameNo
installDependenciesNo
flowReplayBeforeStepsNo
flowReplayMinimumScoreNo
flowReplayTargetCheckpointIdNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0-alpha.14

TDQS

C2.9/5.0
Behavior3/5

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

There are no annotations, so the description carries the full behavioral burden. It does include useful safety signals: [approval required], [device mutation], and [risk:dangerous], plus the overall sequence of actions. However, it does not disclose side effects like app data clearing, repeated iterations, APK building, or evidence collection implications beyond the terse pipeline.

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 compact and front-loaded with critical safety tags, and the arrow-separated pipeline communicates the high-level flow efficiently. It earns its place, though it sacrifices some useful explanatory detail for brevity.

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

Completeness1/5

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

Despite the tool's high complexity (22 parameters, nested objects, no output schema, no annotations), the description is only one line. It does not explain loop semantics, iteration limits, prerequisites like emulator or Appium session setup, or how the many optional parameters alter behavior. This is far from sufficient for an agent to invoke the tool correctly.

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

Parameters1/5

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

Schema description coverage is 0% and the description adds no parameter-level meaning. With 22 parameters including arrays, objects, booleans, and numbers, the agent gets no help understanding how goal, appiumSteps, apiChecks, maxTestIterations, flowReplay*, and the other options relate to the described pipeline.

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 names a specific orchestrated pipeline: build -> install -> Appium scripted test -> verification -> evidence -> loop record, and scopes it to Android. This clearly separates it from the sibling orchestrator.run_ios_validation_loop and from the granular component tools.

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

Usage Guidelines2/5

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

No guidance is provided about when to call this orchestrator versus using the individual build, device, appium, verify, and loop tools directly. The pipeline implies a full validation loop, but there is no explicit when-to-use, when-not-to-use, or alternative selection advice.

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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