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auth_capture

Intercept network requests matching a URL pattern to capture authentication headers (e.g., Authorization, Cookie) from browser memory.

Instructions

⭐ Intercept the next N requests matching a URL pattern and return their headers (Authorization, Cookie, X-CSRF-*, etc.) — useful for SPAs that hold bearer tokens in JS memory and never write them to localStorage.

Pattern: substring match on URL (case-sensitive). For regex use
network_get instead.

Args:
    filter_url_pattern: e.g. "/api/" or "graphql"
    count: stop capturing after this many matches (default 1)
    timeout: max seconds to wait (default 10)
    include_response_headers: also wait for + return response headers

Returns JSON array of {url, method, request_headers, request_body,
[response_headers, status]}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filter_url_patternYes
countNo
timeoutNo
include_response_headersNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description thoroughly discloses behavior: intercepts requests, stops after count matches, has timeout, optionally includes response headers, and returns a JSON array.

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 brief intro, pattern note, argument list, and return format. A star emoji adds minimal verbosity but doesn't detract.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity and no annotations, the description covers all necessary aspects: use case, pattern details, parameters, and return format, making it fully informative.

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 0%, so description compensates by explaining each parameter's purpose and defaults, adding value beyond raw 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 the tool intercepts requests matching a URL pattern to capture headers, and explicitly distinguishes from sibling tool network_get for regex matching.

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?

It provides explicit context for when to use (SPAs with bearer tokens in JS memory) and when not to (use network_get for regex), plus pattern matching details.

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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