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capture_auth_session

Capture browser authentication sessions by opening a headed browser for manual OAuth/MFA login, then save the storage state for reuse in automated workflows.

Instructions

Open a headed browser for interactive OAuth/MFA login and save the session state.

A browser window opens — complete Google/GitHub OAuth or any MFA flow manually. The tool polls the URL every 500ms and saves storage state automatically once login succeeds.

Args: profile_name: Name to save the auth profile under login_url: URL of the login page to open success_url_pattern: URL substring that indicates successful login (e.g. "/dashboard") If omitted, any URL change away from login_url counts as success timeout_secs: Max seconds to wait for login (default: 120) user_data_dir: Optional path to a persistent Chromium profile dir (for OAuth providers that detect fresh browser contexts as bots, e.g. Google, LinkedIn)

Returns: dict with profile_name, requested_profile_name, status ("captured" | "timeout" | "error"), storage_state_path, note

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
login_urlYes
profile_nameYes
timeout_secsNo
user_data_dirNo
success_url_patternNo
Behavior5/5

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

With no annotations, the description carries full burden and delivers: it discloses the headed browser behavior, polling interval (500ms), automatic storage state save, success detection via URL pattern or any URL change, timeout default, and the return statuses ('captured' | 'timeout' | 'error'). This is rich behavioral disclosure.

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 well-structured with a clear overview, an Args block, and a Returns block. Every sentence adds relevant information, with no filler or redundant repetition of schema details.

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?

For a complex interactive browser tool with 5 parameters and no output schema, the description covers the full flow: setup, behavior, success criteria, and return format. It provides everything an agent needs to invoke and interpret the tool correctly.

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?

Schema description coverage is 0%, but the description fully compensates by explaining every parameter: profile_name's purpose, login_url, success_url_pattern with its default behavior, timeout_secs with default, and user_data_dir with rationale for OAuth providers. This adds significant meaning beyond the bare 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's function: 'Open a headed browser for interactive OAuth/MFA login and save the session state.' This specific verb+resource phrasing distinguishes it from siblings like 'save_auth_profile' and 'capture_artifact'.

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 provides clear context for when to use the tool (interactive OAuth/MFA flows that require manual login) and includes practical details like using user_data_dir for providers that detect bots. However, it doesn't explicitly name alternatives or state when not to use it, so it stops short of full explicit guidance.

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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