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by LvcidPsyche
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

browser.activate_tab

Brings a chosen tab to the foreground by its zero-based index, making it the target for subsequent observations and actions. Returns the activated index, updated session summary, and current tab list.

Instructions

Bring one tab to the foreground so subsequent observations and actions target it. Tab indexes come from browser.list_tabs. Returns the activated index, the updated session summary, and the current tab list.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
indexYesZero-based index of the target tab, as reported by browser.list_tabs.
session_idNoTarget session id, from browser.create_session or browser.list_sessions. Optional when exactly one session is live; observe and act tools create one when none is.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.8.1
  2. Removedv1.4.2
  3. Changed2 schema fields changedv1.4.2
    • addedInput schema / properties / index / description
      Added value: +"Zero-based index of the target tab, as reported by browser.list_tabs."
    • addedInput schema / properties / session_id / description
      Added value: +"ID of the target browser session, as returned by browser.create_session or listed by browser.list_sessions."
  4. Changed3 schema fields changedv1.0.3
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / session_id / maxLength
      Added value: +120
    • addedInput schema / properties / session_id / minLength
      Added value: +1
  5. First observedv0.5.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already establish the mutation profile (readOnlyHint=false, idempotentHint=false), so the bar is lower. The description adds useful behavior beyond annotations: it changes the foreground target for later calls and documents the return payload (index, session summary, tab list). No contradiction with annotations.

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 short sentences with the main purpose front-loaded and no filler. Every clause earns its place: what it does, why, where the parameter comes from, and what it returns.

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?

For a low-complexity tool with two well-described parameters, no output schema, and annotations, the description's mention of return values compensates for the missing output schema. The only omission, error behavior on invalid index, is minor and inferable from the schema's minimum constraint.

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 coverage is 100%, so the schema fully documents index and session_id. The description reinforces only that indexes come from browser.list_tabs and adds no new semantics beyond what the schema already provides, so baseline 3 is appropriate.

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?

States exactly what it does ('Bring one tab to the foreground') and why ('so subsequent observations and actions target it'), clearly distinguishing it from siblings like browser.list_tabs and browser.close_tab. The verb-resource pairing is specific and unambiguous.

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?

Gives an explicit workflow: tab indexes come from browser.list_tabs, and activation is for targeting subsequent observations and actions. It does not enumerate exclusions or name alternative tools, but the context is clear enough to choose it over tab-listing and tab-closing siblings.

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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