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find_elements

Search iOS Simulator UI elements by text in labels, values, or hints to locate interface components for automation tasks.

Instructions

Search the UI tree for elements whose label, value, or hint contains query text

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesText to search for in labels/values/hints
udidNoSimulator UDID (optional, defaults to booted simulator)

Implementation Reference

  • Implementation of the 'find_elements' MCP tool handler.
    private async findElements(query: string, udid?: string) {
      const target = await resolveUdid(udid);
      try {
        const all = await this.fetchUiTree(target);
        const matches = findElementsByText(all, query);
        return {
          content: [{
            type: 'text',
            text: JSON.stringify({ query, count: matches.length, elements: matches }, null, 2),
          }],
        };
      } catch (error: any) {
        throw new McpError(ErrorCode.InternalError, `Failed to find elements: ${error.message}`);
      }
    }
  • src/index.ts:446-455 (registration)
    Registration of the 'find_elements' tool with its schema definition.
    {
      name: 'find_elements',
      description: 'Search the UI tree for elements whose label, value, or hint contains query text',
      inputSchema: {
        type: 'object',
        properties: {
          query: { type: 'string', description: 'Text to search for in labels/values/hints' },
          udid: { type: 'string', description: 'Simulator UDID (optional, defaults to booted simulator)' },
        },
        required: ['query'],
Behavior2/5

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

With no annotations, the description carries full burden but provides minimal behavioral insight. It mentions searching UI elements but doesn't disclose critical traits like whether this is read-only (implied but not stated), performance considerations, error handling, or output format (e.g., list of elements). This leaves gaps for safe and effective use.

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 a single, efficient sentence with zero waste. It front-loads the core purpose ('Search the UI tree for elements') and specifies the search criteria concisely, making it easy to parse quickly.

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?

Given no annotations and no output schema, the description is incomplete for a search tool. It lacks details on behavioral aspects (e.g., read-only nature, result format) and doesn't compensate for the absence of structured output information, leaving the agent uncertain about what to expect from the tool.

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%, so parameters are well-documented in the schema. The description adds no additional meaning beyond implying the 'query' searches across labels, values, and hints, which is already covered in the schema's description for 'query'. Baseline 3 is appropriate as the schema does the heavy lifting.

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 action ('Search') and target ('UI tree for elements'), specifying the search criteria ('label, value, or hint contains query text'). It distinguishes from siblings like get_ui_tree (which retrieves the entire tree) or tap_text (which interacts with text), but doesn't explicitly differentiate from hypothetical similar search 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 on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a booted simulator or launched app), exclusions, or comparisons to siblings like get_ui_tree for broader inspection or tap_text for direct interaction.

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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