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act_on

Resolve a unique visible element by reference or accessible meaning, perform a single interaction like click or set_value, and return an observation receipt—all in one governed call. Ambiguous matches are reported without acting.

Instructions

Resolve one visible element by ref or accessible meaning, perform one action, and return a bounded observation receipt. Use this when the target should be unique and you want to avoid a separate find, action, and wait loop. Ambiguous semantic matches are reported without acting.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tabIdYesTab ID containing the target. Use tabs_context first if you do not have one.
valueNoValue for set_value only.
actionYesOne interaction to perform after unique target resolution.
expectNoOptional postcondition. Provide exactly one of selector or text; the action and observation remain one governed call.
targetYesExactly one of ref, query, or name. A semantic tie is returned without acting.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
waitNo
candidatesNo
provenanceNo
interactionReceiptNo
Behavior4/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It discloses that exactly one action is performed, a bounded observation receipt is returned, and ambiguity prevents action. However, it does not elaborate on side effects, permissions, or failure modes beyond ambiguity, which keeps it from a 5.

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 consists of three concise sentences, with the purpose front-loaded. Every sentence adds value—defining the action, usage context, and ambiguity behavior—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 tool has 5 parameters, nested objects, an action enum, and an optional expect postcondition. The description covers unique targeting, ambiguity handling, and the bounded receipt, which are the non-obvious behaviors. The schema and output schema handle the remaining parameter and return details, so the description is sufficiently complete.

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?

The input schema already provides 100% description coverage for all parameters, including detailed notes on target ('Exactly one of ref, query, or name') and expect. The description only reinforces the concept of 'ref or accessible meaning' without adding new parameter-level syntax or constraints.

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 states the tool's function: 'Resolve one visible element by ref or accessible meaning, perform one action, and return a bounded observation receipt.' It uses a specific verb (resolve, perform, return) and resource (visible element), and distinguishes itself from a separate find, action, and wait loop.

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?

Explicit guidance is given: 'Use this when the target should be unique and you want to avoid a separate find, action, and wait loop.' It also signals a when-not case by stating that ambiguous semantic matches are reported without acting.

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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