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get_active_tabs

Retrieves details of open tabs in VS Code to provide the AI agent with project context, with an option to include file contents.

Instructions

Retrieves information about currently open tabs in VS Code to provide context for the AI agent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetProjectPathYesPath to the project folder we are working in
includeContentNoWhether to include the file content of each tab (may be large)
Behavior2/5

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

No annotations are present, so the description fully bears the burden of disclosing behavior. It only states 'Retrieves' (implying read-only) but lacks details on side effects, permissions, or performance implications. The agent cannot assess safety or cost.

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 a single sentence with no wasted words. However, it could be more impactful by adding specific usage context. It is appropriately size for the tool's simplicity.

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?

The description does not explain what information is returned (e.g., tab paths, titles, content). With no output schema, the agent is left guessing. The sibling 'get_context_tabs' may return similar data, increasing ambiguity.

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 covers 100% of parameters with descriptions. The description adds minimal new meaning beyond the schema, such as noting that context is provided for the AI agent. This meets the baseline but does not enhance agent understanding.

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 verb 'Retrieves' and the resource 'currently open tabs in VS Code', making the purpose explicit. However, it does not differentiate from the sibling tool 'get_context_tabs', which may have overlapping functionality.

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. There is no mention of prerequisites, context, or exclusions, leaving the agent without decision support.

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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