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run_macro

Execute multiple desktop automation steps sequentially in one call to reduce latency for predictable workflows like focus, type, and screenshot operations.

Instructions

Purpose: Execute multiple tools sequentially in one MCP call — eliminates round-trip latency for predictable multi-step workflows. Details: steps[] is an array of {tool, params} objects. Accepts all desktop-touch tools plus a special sleep pseudo-step: {tool:"sleep", params:{ms:N}} (max 10000ms per step). stop_on_error=true (default) halts on first failure. Max 50 steps. The LLM cannot inspect intermediate results during execution — all steps run to completion (or first error) before any output is returned. Prefer: Use for predictable fixed sequences (focus → sleep → type → screenshot). Do not use for conditional logic — return to the LLM between branches so it can inspect intermediate state. Caveats: If any step may fail conditionally (e.g. a dialog that may or may not appear), split the macro at that point. Each screenshot step within a macro incurs the same token cost as a standalone call. Examples: [{tool:'focus_window',params:{windowTitle:'Notepad'}},{tool:'sleep',params:{ms:300}},{tool:'keyboard_type',params:{text:'Hello'}},{tool:'screenshot',params:{detail:'text',windowTitle:'Notepad'}}] [{tool:'browser_navigate',params:{url:'https://example.com'}},{tool:'wait_until',params:{condition:'element_matches',target:{by:'text',pattern:'Example Domain'}}}]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stepsNoOrdered list of tool calls to execute sequentially (max 50 steps).
stop_on_errorNoStop execution on the first error (default true). Set false to collect all results.
Behavior5/5

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

With no annotations provided, the description carries full burden and excels at disclosing behavioral traits. It explains execution flow ('all steps run to completion before any output is returned'), error handling ('stop_on_error=true (default) halts on first failure'), constraints ('Max 50 steps', 'max 10000ms per step'), special pseudo-steps ('sleep'), and performance implications ('token cost as a standalone call').

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 well-structured with clear sections (Purpose, Details, Prefer, Caveats, Examples) and every sentence adds value. It could be slightly more concise in the examples section, but overall it's efficiently written with no wasted words and front-loads the most important information.

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

Completeness5/5

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

Given the tool's complexity (multi-step execution with special behaviors) and absence of both annotations and output schema, the description provides comprehensive context. It covers purpose, usage guidelines, behavioral details, parameter semantics, constraints, examples, and caveats - everything needed for an agent to understand and use this tool correctly.

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?

Schema description coverage is 100%, so baseline is 3. The description adds significant value beyond the schema by explaining the structure of steps[] ('array of {tool, params} objects'), special pseudo-step syntax, and practical examples showing how parameters are used. However, it doesn't provide additional semantics for stop_on_error beyond what's in the schema.

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 explicitly states the purpose as 'Execute multiple tools sequentially in one MCP call' with clear differentiation from sibling tools. It specifies this eliminates round-trip latency for predictable multi-step workflows, distinguishing it from individual tool calls or conditional workflows handled by the LLM.

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use ('Prefer: Use for predictable fixed sequences') and when not to use ('Do not use for conditional logic — return to the LLM between branches'). It also mentions specific alternatives ('split the macro at that point') and caveats about conditional failures and token costs for screenshots.

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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