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act

Destructive

Automate multi-step browser workflows by describing actions in natural language. Parses and executes clicks, typing, navigation, and more in sequence.

Instructions

Execute multi-step browser actions from a natural language instruction. Parses and runs click, type, select, scroll, hover, navigate, and wait steps in sequence.

When to use: Automating a known multi-step flow (login, form fill, navigation) in one call. When NOT to use: Use interact for a single element action, or computer for raw coordinate input.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tabIdYesTab ID to execute on
instructionYesNatural language description of actions (e.g., "click login, type admin in username, click submit")
contextNoAdditional context (e.g., "on the login page")
verifyNoVerify mode. boolean is legacy: true→"screenshot", false→"none". String enum returns a compact diff signal (AX-hash delta + pHash, ≤4KB).
timeoutNoMax time in ms for entire sequence. Default: 30000
use_workflow_cacheNoOpt-in: try guarded structured workflow cache before legacy action cache. Default: false
record_workflow_cacheNoOpt-in: record safe successful parsed sequences into the structured workflow cache. Default: false
allow_risky_replayNoAllow replay of workflow cache entries marked risky. Default: false
workflow_debugNoInclude concise workflow cache accept/reject metadata in the response. Default: false
returnAfterStateNoOptional chaining hint. When "ax" or "dom", the response includes a page snapshot of that mode captured after the post-action wait, removing the need for a follow-up read_page call. Default: "none".
Behavior4/5

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

Annotations already convey destructiveHint=true and readOnlyHint=false. The description adds context about parsing instructions and sequential execution, which is consistent with annotations. No contradictions.

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?

Two concise sentences plus two usage lines. No wasted words, front-loaded with purpose, then usage guidance. Efficient and well-structured.

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?

With 10 parameters (100% schema coverage) and no output schema, the description covers core functionality and usage context. Could mention caching parameters but not necessary given schema detail. Adequate for complexity.

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 coverage is 100% with detailed parameter descriptions. The description adds value by listing the types of actions parsed (click, type, etc.), which is not in the schema, enhancing understanding of the 'instruction' parameter.

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 executing multi-step browser actions from natural language, listing specific actions (click, type, etc.), and distinguishes from siblings by specifying when to use 'interact' or 'computer' instead.

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?

Explicitly states when to use (automating a known multi-step flow) and when not to use (single element action→interact, raw coordinate→computer), providing clear alternatives and guidance.

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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