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huaka1
by huaka1

browser_intercept_request

Intercept, block, or mock network requests to control API responses, block ads or tracking, and test error handling by simulating network failures.

Instructions

Intercept, block, or mock network requests matching a URL pattern.

Use this to:

  • Block requests (e.g., block ads, tracking scripts)

  • Mock API responses (return custom JSON)

  • Test error handling (simulate network failures)

Args: url_pattern: URL pattern to match (e.g., "/api/*", "/analytics/*") action: "block" to abort matching requests, "mock" to return custom response response_body: JSON string for mock responses (only used when action="mock") session_id: Browser session ID

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionNoblock
session_idNodefault
url_patternYes
response_bodyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It explains the actions ('block' aborts, 'mock' returns custom response) but does not disclose important behavioral details like persistence of intercepts, scope (per-session or global), or how to revert them.

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 concise (about 5 lines), uses bullet points for use cases and parameter list, and front-loads the purpose. Every sentence adds value with no redundancy.

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 the tool's moderate complexity and the existence of an output schema (which handles return values), the description covers essential aspects. However, it omits details about cleaning up intercepts or session-level behavior, which could be important for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, but the description thoroughly explains all four parameters: url_pattern (URL pattern), action (block/mock), response_body (for mock), and session_id. It adds meaningful semantic context beyond the schema's titles and defaults.

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 the tool intercepts, blocks, or mocks network requests, listing specific use cases like blocking ads or mocking API responses. This distinguishes it from sibling tools that handle browsing actions like navigation or clicking.

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?

The description includes a 'Use this to' section with bullet points for three explicit scenarios. It provides clear guidance on when to use, though it does not mention when not to use or suggest alternatives.

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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