env_opened
Lists currently active browser environments to monitor and manage open sessions for automation workflows.
Instructions
查询当前已打开环境列表
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Lists currently active browser environments to monitor and manage open sessions for automation workflows.
查询当前已打开环境列表
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool queries opened environments, implying a read-only operation, but doesn't specify if it requires authentication, returns paginated results, has rate limits, or what the output format might be. For a tool with zero annotation coverage, this is a significant gap in transparency about how it behaves beyond the basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence: '查询当前已打开环境列表' (query current opened environment list). It's front-loaded with the core purpose, has zero wasted words, and is appropriately sized for a simple query tool. Every part of the sentence earns its place by specifying what is being queried.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a query operation with no parameters) and the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'opened environment' means in this context, what the return values might include (e.g., list format, fields), or any behavioral constraints. For a tool with no structured data to rely on, the description should provide more context to be fully helpful to an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100% (since there are no parameters to describe). With no parameters, the description doesn't need to add semantic details beyond what the schema provides. The baseline for 0 parameters is 4, as there's nothing to compensate for, and the description adequately conveys the tool's purpose without parameter confusion.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as '查询当前已打开环境列表' (query current opened environment list), which specifies the verb (query) and resource (opened environment list). It distinguishes from siblings like env_create (create) and env_terminate (terminate) by focusing on listing rather than modifying. However, it doesn't explicitly differentiate from env_query (which might query environments more broadly) or env_runtime_state (which might provide runtime details), keeping it from a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose env_opened over env_query (which might query all environments, not just opened ones) or env_runtime_state (which might include state details). There's no context on prerequisites, exclusions, or typical use cases, leaving the agent to infer usage from the name and description alone.
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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