android-dev-mcp

scaffold_feature

Fetches project conventions and live dependency versions to generate an Android CLI scaffold command for creating a new feature.

Instructions

Agentic workflow: loads ITGD conventions + fetches live versions + scaffolds a new feature. Returns the context + version data + Android CLI scaffold command for Claude to execute. Steps: get_full_context → get_live_versions → android create guidance.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "feature_name": "<feature_name>"
    },
    "name": "scaffold_feature"
  }
}

Input Schema

Name	Required	Description	Default
`template`	No	Android CLI template name. Defaults to 'empty-activity-agp-9'.
`feature_name`	Yes	Name of the feature to scaffold (e.g. 'PlayerScreen', 'SearchFeature').

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.1.1Aug 2, 2026

TDQS

A4.2/5.0

Behavior4/5

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

With no annotations, the description discloses a key behavioral trait: the tool returns a scaffold command for Claude to execute rather than executing it directly. It also lists the workflow steps. It does not detail side effects, permissions, or failure modes, but the core non-execution behavior is clearly stated.

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 concise and front-loaded, using two sentences to convey the workflow, return value, and step sequence. Every phrase adds value with no redundancy.

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?

The description covers the tool's purpose, return value (context, version data, command), and workflow steps. Without an output schema, it lacks detailed structure of the returned data, but it provides sufficient guidance for an agent to know what to expect and that the command should be executed later.

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?

Both parameters (feature_name and template) are fully described in the schema with clear explanations and a default for template. The description adds no additional parameter context, but schema coverage is 100%, 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 clearly defines the tool as an agentic workflow that loads ITGD conventions, fetches live versions, and scaffolds a new feature by returning a CLI command. It distinguishes itself from sibling tools like get_full_context and get_live_versions by being a composite orchestration step.

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 implies usage by showing the workflow steps (get_full_context → get_live_versions → android create guidance), indicating this is for end-to-end scaffolding. However, it does not explicitly state when to use this instead of running the steps individually or provide alternative tool comparisons.

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