Skip to main content
Glama

wait_for

Pauses automation until specific text or CSS selector appears on a webpage, ensuring reliable interaction timing for human-like browsing behavior.

Instructions

Wait for text or selector to appear on the page

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageIdNoPage ID (uses active page if not specified)
textNoText to wait for
selectorNoCSS selector to wait for
stateNovisible
timeoutNoTimeout in milliseconds
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. While 'wait for' implies a blocking operation, it doesn't describe what happens on timeout, whether it polls continuously, what the return value indicates, or any performance implications. The description lacks critical behavioral details needed for proper tool invocation.

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 is a single, efficient sentence that gets straight to the point with zero wasted words. It's perfectly front-loaded with the core functionality, making it immediately comprehensible without any unnecessary elaboration.

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?

For a 5-parameter tool with no annotations and no output schema, the description is inadequate. It doesn't explain what constitutes 'appear on the page', what happens when the condition isn't met, what the tool returns, or error conditions. The lack of behavioral context makes this incomplete for proper agent understanding.

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 description coverage is 80%, providing a solid baseline. The description mentions 'text or selector' which aligns with two parameters, but doesn't explain the relationship between them (mutually exclusive? both required?). It doesn't mention the 'state' parameter's significance or the 'timeout' default behavior, leaving gaps despite good schema coverage.

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 tool's purpose with a specific verb ('wait for') and target ('text or selector to appear on the page'), making it immediately understandable. It doesn't explicitly distinguish from sibling tools like 'wait_for_navigation', but the focus on page elements rather than navigation events provides implicit differentiation.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'wait_for_navigation' for navigation-based waiting or clarify whether this is for dynamic content loading versus static element detection. There's no context about prerequisites or typical use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/baixianger/camoufox-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server