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Rorogogogo

jobjourney-claude-plugin

by Rorogogogo

login_jobsite

Log in to SEEK or LinkedIn to save cookies for future job scrapes, enabling access to full descriptions, salary, and applied status.

Instructions

Open a browser window for the user to log in to a job site (SEEK or LinkedIn). Saves cookies so future scrapes can access full job details including descriptions, salary, and applied status. Run this once per site before scraping.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteYesJob site to log in to: 'seek' or 'linkedin'

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.2.5

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and discloses key traits: it opens a browser for user interaction, saves cookies, and enables future scrapes to access full job details. It also notes the once-per-site usage pattern. It does not cover what happens if already logged in, browser blocking behavior, or error cases, but it provides substantial behavioral context.

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?

Three sentences, each earning its place: purpose first, then the side effect and benefit, then the usage instruction. It is front-loaded and free of redundant detail.

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 simple one-parameter schema, no annotations, and no output schema, the description covers purpose, key side effect, and usage timing well. An agent can determine when and how to call it. Some minor gaps remain around return behavior and edge cases, but no structured field is left unexplained.

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 100%, and the schema itself documents the single 'site' parameter with allowed values 'seek' or 'linkedin'. The description mentions SEEK or LinkedIn but adds no syntax, format, or meaning beyond what the schema already provides, so the baseline of 3 applies.

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 states a specific verb and resource: 'Open a browser window for the user to log in to a job site (SEEK or LinkedIn).' It names the supported sites and clearly distinguishes this login action from sibling tools like check_login_status, which checks status rather than performing login.

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?

It gives a clear timing instruction: 'Run this once per site before scraping.' This tells the agent when to invoke the tool. However, it does not explicitly state when not to use it or name an alternative for checking existing login state.

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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