JobSelect Labs
Sign in

JOBSELECT LABS / DOCS

JobSelect Documentation

Everything you need to analyze job descriptions, use JobSelect from the terminal, integrate the hosted API, and understand JobAnalyze 6k.

Ctrl K

BROWSER

Analyze in the browser

Use the Web Job Analyzer without installing anything.

Open Job Analyzer →

CLI

Install the CLI

pip install jobselect

API

Use the API

Send Job Description + Role + Type and receive ranked skills.

API Quickstart →

Introduction

JobSelect is an AI-powered job analysis platform developed by JobSelect Labs. It provides tools for analyzing job descriptions, extracting technical skills, evaluating candidate fit, and integrating job intelligence into developer workflows.

The JobSelect platform includes JobAnalyze 6k, the JobSelect CLI, Web Analyzer, hosted API, and MCP integration.

Job Description → JobAnalyze 6k
                    ├─ Web Job Analyzer
                    ├─ JobSelect CLI
                    ├─ Hosted API
                    └─ MCP workflows

Installation

Install the published Python package, then launch the CLI.

pip install jobselect
jobselect

Overview

JobSelect CLI is the terminal/TUI interface for JobAnalyze 6k. It provides a focused workflow for entering a job description, selecting a role and selecting a job type before running an analysis.

Cloud/API mode

Uses the hosted JobAnalyze service when a valid API key is configured.

Local mode

Uses the local model path when the required model artifacts are available on the machine.

The exact model artifacts and API availability depend on the installed JobSelect release and local configuration.

First launch

On first launch, JobSelect presents a connection screen for choosing how inference should run. The screen provides an API-key input, a Connect action, and a Run Locally action.

When an API key is configured, the CLI saves it locally under ~/.jobselect/.env so subsequent sessions can reuse it. Never expose a real API key in documentation or screenshots.

Interactive analysis

The main screen provides fields for Job Description, Job Role, and Job Type, followed by Analyze Job Description and Clear.

Keyboard shortcuts

KeyAction
TabMove focus to the next field or button
Shift+TabMove focus to the previous field or button
qQuit
EscFocus Job Description
Ctrl+RFocus Role
Ctrl+TFocus Type
Ctrl+POpen command palette

Keyboard navigation

You can navigate the main CLI screen entirely from the keyboard. Press Tab to move forward through the Job Description field, Job Role, Job Type, Analyze Job Description, and Clear. Use Shift+Tab to move backward through the same controls.

API mode

API mode sends the analysis request to the hosted JobAnalyze service. A valid API key is required for authenticated CLI API requests.

Local mode

Local mode runs the model from locally available artifacts. It is useful when you want inference without sending the job description to the hosted API.

API key storage

The CLI stores the configured API key in ~/.jobselect/.env. Treat this file as a secret and do not commit or share it.

JobAnalyze 6k

JobAnalyze 6k is the skill-classification model used by JobSelect. It combines TF-IDF features with a PyTorch MLP to classify technical and soft skills from job descriptions.

Hosted API

The hosted API accepts a job description, role, and job type and returns the model's analysis.

Errors

For API errors, check the request schema, authentication key, and server response status.

MCP Integration

JobSelect exposes the JobAnalyze service through an HTTP MCP endpoint. MCP-compatible clients can connect to the hosted endpoint and use JobAnalyze with an API key supplied through the MCP request headers.

Configuration

Add the following server configuration to an MCP client that supports HTTP servers.

{
  "mcpServers": {
    "jobanalyze": {
      "type": "http",
      "url": "https://job-description-analysis.onrender.com/mcp",
      "headers": {
        "JobAnalyze_6k_Key": "ja6k_yourkey"
      }
    }
  }
}

What MCP is used for

MCP allows compatible AI clients and agents to connect to JobAnalyze as a remote tool instead of requiring the model or API integration to be implemented directly in each client.

AI-agent workflow

Configure the HTTP MCP server, provide a valid JobAnalyze API key, and let the MCP client discover and invoke the available JobAnalyze capabilities as part of an agent workflow.

Configuration values

typeHTTP MCP server
urlhttps://job-description-analysis.onrender.com/mcp
JobAnalyze_6k_KeyYour JobAnalyze API key, for example ja6k_yourkey.

Troubleshooting

  • • Verify that the MCP client supports remote HTTP MCP servers.
  • • Check that the server URL is exactly https://job-description-analysis.onrender.com/mcp.
  • • Make sure JobAnalyze_6k_Key contains a valid JobAnalyze API key.
  • • If authentication fails, generate or retrieve a valid API key from your JobSelect account.

Dataset

The documented published dataset contains 609 rows.

roletypejob_descyearqualificationexperiencetech_skillssoft_skills
View Dataset

Evaluation

Micro-F1

0.624

Macro-F1

0.420

Baseline Micro-F1

0.538

Baseline Macro-F1

0.152

93.34% recall (14/15) is a documented sample inference result, not universal accuracy.

Limitations

Fixed vocabulary

Predictions are constrained to the documented skill vocabulary.

Dataset coverage

Performance depends on labelled-data coverage and quality.

No hiring prediction

The model analyzes requirements; it does not predict employer hiring decisions.

Probability interpretation

Model scores should not automatically be treated as calibrated real-world probabilities.

FAQ