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Open the Prompt Lab web UI to create or connect to a workspace for prompt optimization and testing. Provide API keys to enable the Send button.

Instructions

Open the prompt lab web UI. Returns the URL for the browser.

If no workspaceId is given, creates a new empty workspace. If workspaceId is given, connects to that workspace (must exist).

Always pass your environment API keys — they enable the UI Send button. Check each env var and pass it if set: anthropicApiKey: process.env.ANTHROPIC_API_KEY geminiApiKey: process.env.GEMINI_API_KEY openaiApiKey: process.env.OPENAI_API_KEY

After returning the URL, call list_models to register available models. Then set_system_prompt and add_test_cases before running optimization.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspaceIdNoExisting workspace ID. Omit to create a new workspace.
labelNoLabel for new workspace (ignored if workspaceId given)
anthropicApiKeyNo
geminiApiKeyNo
openaiApiKeyNo
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses workspace creation/connection behavior, URL return, and API key requirement. However, it doesn't mention if the tool modifies state beyond workspace creation or any rate limits.

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?

Well-structured with bullet-like list for API keys. Every sentence adds value. Slightly verbose in the step-by-step guidance, but overall efficient and front-loaded.

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?

Given 5 parameters and no output schema, description covers creation vs connection, API key usage, and subsequent workflow steps. Return value described as 'URL for the browser' suffices. Could be more complete on potential side effects, but adequate.

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 40% with descriptions for workspaceId and label. Description extensively covers the three API key parameters: explains they enable UI Send button, how to check env vars, and which keys to pass. This adds significant meaning beyond the schema.

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 'Open the prompt lab web UI' with a specific verb and resource. It distinguishes itself from siblings by focusing on UI launch, while sibling tools like list_models, set_system_prompt are for subsequent steps.

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?

Provides explicit when-to-use: create new workspace vs connect existing. Includes post-invocation steps: 'After returning the URL, call list_models... then set_system_prompt and add_test_cases'. Also instructs to always pass API keys, explaining why.

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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