JustHireMe

Local-first AI job intelligence for scraping better roles, ranking fit, and generating tailored application materials.

What It Does · Workflow · Architecture · Quick Start · Standard Procedure · Agent Skill + MCP · Contributing · Roadmap

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Star History

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The Short Version

JustHireMe is an AGPL-licensed, local-first desktop workbench for people who are tired of noisy job boards and black-box AI apply tools.

Maintainer

JustHireMe is built and maintained by Vasudev Siddh - full-stack AI engineer, open-source builder, and the person who got tired of bad job boards and built something better.

Sponsor the project - Sponsorship keeps JustHireMe actively maintained, funds source adapter coverage, and supports the local-first architecture that makes this different from every cloud-first alternative.

Current Status

JustHireMe's stable core is the local-first desktop workbench, Python sidecar API, lead ingestion, deterministic ranking, profile-aware matching, local CRM workflows, and document/outreach generation. Every release is built by GitHub Actions from a v* tag and now ships installers for Windows, macOS, and Linux.

If you are new here, start with the frontend preview first. If you want to contribute backend behavior, source adapters, or packaging, use the full desktop setup below.

It helps you:

Browser automation and auto-apply code exists in the repository, but it is experimental, opt-in, and unsupported as part of the stable core. The supported open-source core is scraper, ranker, vector matching, and customizer.

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Visual Workflow

flowchart LR
    A["Import Resume / Profile"] --> B["Profile Graph<br/>Kuzu"]
    A --> C["Skill + Project Vectors<br/>LanceDB"]
    D["Scraper Sources"] --> E["Normalized Leads"]
    E --> F["Lead Quality Gate"]
    F --> G["Ranker + Evaluator"]
    B --> G
    C --> G
    G --> H["Lead Pipeline"]
    H --> I["Customizer"]
    I --> J["Resume PDF"]
    I --> K["Cover Letter PDF"]
    I --> L["Outreach Drafts"]

flowchart TD
    S["Source Adapter"] --> N["Normalize Lead"]
    N --> Q{"Quality Gate"}
    Q -- "Reject" --> R["Filtered with reason"]
    Q -- "Accept" --> C["Local CRM"]
    C --> E["Fit Evaluation"]
    E --> U["User Review"]

    Q:::gate
    R:::reject
    C:::store
    E:::score

    classDef gate fill:#e0f2fe,stroke:#0284c7,color:#0f172a
    classDef reject fill:#fee2e2,stroke:#dc2626,color:#0f172a
    classDef store fill:#dcfce7,stroke:#16a34a,color:#0f172a
    classDef score fill:#fef3c7,stroke:#d97706,color:#0f172a

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What It Does

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Why This Exists

Most job search tools make one of two mistakes:

JustHireMe takes a different path:

More signal.
More explanation.
More local control.
More contributor-friendly source adapters.
Less blind automation.

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Product Principles

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Architecture

flowchart TB
    subgraph Desktop["Tauri Desktop Shell"]
        UI["React + TypeScript UI"]
        Bridge["Tauri Commands<br/>Port + API Token"]
    end

    subgraph Backend["Python Backend Sidecar"]
        API["FastAPI + WebSockets"]
        Scrapers["Scraper Agents"]
        Gate["Lead Quality Gate"]
        Ranker["Ranker / Evaluator"]
        Customizer["Document + Outreach Generator"]
    end

    subgraph LocalData["Local Data Layer"]
        SQLite["SQLite CRM"]
        Kuzu["Kuzu Profile Graph"]
        LanceDB["LanceDB Vectors"]
        Files["Generated PDFs"]
    end

    UI --> Bridge --> API
    API --> Scrapers --> Gate --> SQLite
    API --> Ranker
    Ranker --> Kuzu
    Ranker --> LanceDB
    API --> Customizer --> Files
    API --> SQLite

First-run runtime pack. To keep installers small (~100 MB instead of ~450-700 MB), the heavy runtime - the Playwright browser, vector libraries, and the ONNX embedding model - is not bundled into the installer. The app downloads it once on first run, verifies it, and caches it. The pack is content-versioned, so routine app updates reuse the cached pack instead of re-downloading it.

More detail: docs/ARCHITECTURE.md

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Repository Map

JustHireMe/
|-- src/                         React frontend workbench
|   |-- api/                     HTTP/WebSocket API clients and types
|   |-- features/                Activity, apply, dashboard, graph, inbox, pipeline, profile, settings
|   |-- shared/                  Components, hooks, context, utilities
|   `-- main.tsx                 Frontend entrypoint
|-- backend/                     Python FastAPI sidecar
|   |-- api/                     FastAPI app, routers, auth, scheduler, WebSockets
|   |-- automation/              Scout scraping orchestration + experimental apply/actuator
|   |-- core/                    Config, occupation vocab, SSRF guard, telemetry
|   |-- data/                    SQLite repos, Kùzu graph, LanceDB vectors, migrations
|   |-- discovery/               Query generation, dedup, quality gate, source adapters
|   |-- gateway/                 Async job tracking, discovery config
|   |-- generation/              Resume, cover letter, and outreach generators
|   |-- graph_service/           Query helpers behind the knowledge-graph view
|   |-- llm/                     Provider abstraction (keyed + keyless/subscription-CLI), embeddings
|   |-- profile/                 Resume/LinkedIn/GitHub/portfolio ingestion + normalization
|   |-- ranking/                 Fit scoring, criteria, semantic/evaluator logic
|   `-- tests/                   Backend unit, integration, and regression tests
|-- src-tauri/                   Tauri Rust shell
|   `-- resources/               Bundled sidecar/runtime resources generated for packages
|-- website/                     Public website
|-- docs/                        Architecture, source adapter, release docs
|-- scripts/                     Build scripts
|-- skills/                      Agent skill instructions
`-- .github/                    CI, issue templates, PR template

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Quick Start

Install The Desktop App

Use this path if you are not a developer and just want to run JustHireMe. Open the latest GitHub Release and grab the asset for your platform.

First launch downloads the runtime pack. The first time you open the app it fetches the runtime (browser + vector libraries + embedding model) over HTTPS and caches it; this is a one-time download. After that, the app starts offline-ready and routine updates do not re-download it.

The app updates itself automatically from the latest GitHub release. Release notes include SHA256 checksums, and every installer is built by GitHub Actions from the release tag so the published binary matches the repository source.

Requirements

Optional:

• Ollama for local model experiments
• Playwright browser dependencies only for experimental automation work

Fast Frontend Preview

Use this path if you just want to inspect the UI, design direction, or frontend code.

git clone https://github.com/vasu-devs/JustHireMe.git
cd JustHireMe
npm ci
npm run dev

This starts the Vite frontend only. Backend-backed workflows may show empty, mocked, or unavailable states depending on the screen.

Full Desktop Setup

Use this path if you want the Tauri shell and Python backend sidecar.

git clone https://github.com/vasu-devs/JustHireMe.git
cd JustHireMe
npm ci
cd backend
uv sync --dev
cd ..

Then run:

npm run tauri dev

The Tauri shell starts the frontend and launches the Python backend sidecar/dev process.

Install website dependencies only when working on the public website or running the full local check group:

cd website
npm ci
cd ..

Before Opening An Issue

• Check whether the bug is in supported core behavior or experimental automation.
• Remove API keys, cookies, resumes, local databases, and generated private documents from logs or screenshots.
• For source requests, include a public example URL and expected normalized fields.
• For ranking bugs, include the expected score behavior and sanitized job/profile snippets.

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Development Commands

npm run check runs the version check, frontend typecheck, frontend tests, frontend build, website build, backend tests, Rust tests, and Rust check. Run npm ci, cd backend && uv sync --dev, and cd website && npm ci first so every lane has its dependencies.

On Windows PowerShell, use npm.cmd instead of npm if the npm.ps1 shim is blocked by execution policy. If your shell does not support &&, run the cd command and the following command as separate lines.

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Standard Procedure

Use this workflow for normal development and pull requests:

1. Sync from the lockfiles: npm ci, cd backend && uv sync --dev, and cd website && npm ci if the website or full check suite is involved.
2. Keep changes focused. Core product work should preserve local-first storage, explainable ranking, and human-reviewed generation. Browser automation stays experimental and opt-in.
3. Run targeted checks for the area you changed, then run npm run check before opening a PR when practical.
4. Add or update tests for behavior changes. Use backend regression tests for ranking, source, API, storage, and generation changes.
5. Update docs whenever setup, commands, release behavior, user-facing workflows, source adapter contracts, or privacy expectations change.
6. Do not commit .env, API keys, cookies, bearer tokens, private resumes, local databases, graph/vector stores, generated PDFs, app data, or generated sidecar binaries.

Use this release flow for maintainer builds:

1. Bump all versioned files with npm run version:bump -- X.Y.Z.
2. Run local validation with npm run check:all, npm run lint, npm run test:coverage, npm run release:smoke, and npm run smoke:windows-update.
3. Push a vX.Y.Z tag and let GitHub Actions build, sign, verify updater metadata, smoke the Windows installer, generate checksums, and publish release assets from CI.
4. Verify generated updater artifacts with npm run release:verify-updater -- release-assets vX.Y.Z when checking a downloaded CI asset folder.

Detailed release checklists live in docs/MAINTAINER_RELEASE_CHECKLIST.md, docs/windows-release.md, and docs/PRODUCTION_RELEASE_ROADMAP.md.

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Agent Skill And MCP

JustHireMe includes two reusable agent surfaces:

• An agent-neutral skill at skills/justhireme/SKILL.md
• A lightweight stdio MCP server at backend/mcp_server.py

The skill is plain Markdown with YAML frontmatter. It is written to be useful in any AI coding assistant that can load local instructions, including Claude, Codex, IDE agents, and custom agent runners. It tells an agent how to work safely inside this repository: preserve local-first behavior, keep ranking explainable, treat browser automation as experimental, and use the existing backend/frontend patterns.

Use The Skill

Point your agent or assistant at:

skills/justhireme/SKILL.md

If your agent expects skills in a separate directory, copy or symlink the skills/justhireme folder into that tool's skill/instruction location. The skill has no runtime dependency on Codex-specific APIs.

Use The MCP Server

Install backend dependencies first:

cd backend
uv sync --dev
cd ..

Start the MCP server from the repository root on Windows:

backend\.venv\Scripts\python.exe backend\mcp_server.py

Start it on macOS/Linux:

backend/.venv/bin/python backend/mcp_server.py

The MCP server exposes:

Example MCP client configuration:

{
  "mcpServers": {
    "justhireme": {
      "command": "/absolute/path/to/JustHireMe/backend/.venv/bin/python",
      "args": ["/absolute/path/to/JustHireMe/backend/mcp_server.py"],
      "cwd": "/absolute/path/to/JustHireMe"
    }
  }
}

On Windows, use the venv interpreter at backend\\.venv\\Scripts\\python.exe. More detail: docs/MCP.md

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Core Concepts

Source Adapters

Source adapters turn external job sources into normalized lead dictionaries. Implementations live in backend/discovery/sources/ (ATS boards, RSS/Atom, Hacker News, GitHub, Reddit, custom JSON, and a Playwright-backed web fallback); backend/automation/scout.py fans out across them, dedupes, and hands results to the quality gate.

flowchart LR
    A["Raw Source"] --> B["Adapter"]
    B --> C["Normalized Lead"]
    C --> D["Quality Gate"]
    D --> E["Local CRM"]

Read: docs/source-adapters.md

Quality Gate

The gate lives in backend/discovery/quality_gate.py.

It checks:

Ranking

Ranking combines:

• source signal
• lead quality score
• deterministic fit rubric
• seniority caps
• project and stack evidence
• optional LLM-assisted evaluation
• semantic fit when vectors are available
• feedback learning

Vector Matching

flowchart LR
    Resume["Resume / Profile"] --> Graph["Kuzu Graph"]
    Resume --> Embed["Embeddings"]
    Embed --> Vectors["LanceDB"]
    Job["Job Description"] --> Query["Semantic Query"]
    Query --> Vectors
    Vectors --> Fit["Semantic Fit Signal"]
    Graph --> Fit

Customizer

For a strong lead, the customizer produces:

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Configuration And Privacy

Settings are configured inside the desktop app. For v1, API keys are stored in local app settings.

Local data may include:

Do not share screenshots, logs, local app data, issue attachments, or database files that contain API keys, cookies, private resumes, or personal data.

Planned improvement:

• OS keychain-backed API key storage

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Release Builds

Every release builds and publishes installers for Windows, macOS, and Linux from a single v* tag via GitHub Actions - never uploaded from a maintainer workstation. The pipeline builds each platform's sidecar and Tauri installer, runs an auto-update smoke test, generates SHA256 checksums, and publishes the assets. Windows and macOS builds are not yet code-signed/notarized, so the OS may warn on first launch (see the install table above); code signing and macOS notarization are the next packaging milestone.

npm run release:smoke
npm run smoke:windows-update

Use npm run release:windows only for an intentional local package rehearsal when Tauri updater signing variables are available. Use npm run release:linux or npm run release:macos for platform-specific local package builds when you are explicitly testing those paths.

Release smoke test and packaging details: docs/windows-release.md, docs/MAINTAINER_RELEASE_CHECKLIST.md, and docs/PRODUCTION_RELEASE_ROADMAP.md.

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Contributing

The best first contribution path is scraper/source quality.

Start here:

Please do not open public issues with API keys, resumes, cookies, bearer tokens, or database files.

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Experimental Automation

The repository contains browser automation and auto-apply code for experimentation and future plugin work. This is distinct from the scraping scout (backend/automation/scout.py), which is core, supported, and always on — "experimental" here refers specifically to the DOM-fill/vision-based apply actuator, not lead discovery.

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Roadmap

timeline
    title JustHireMe Open-Source Roadmap
    Shipped : Quality gate + source adapter docs
            : Cross-platform installers (Win / macOS / Linux)
            : Thin installer + first-run runtime download
            : Auto-update
            : Light / Dark / System theming
            : Local ONNX embeddings (no API key)
            : Any-field resume tailoring
    Next : Code signing + macOS notarization
         : More ATS adapters and parser fixtures
         : OS keychain support for API keys
    Later : Ranking evaluation dataset
          : Clearer semantic-matching visibility in the UI
          : Optional automation plugin

Near-term priorities:

• code signing for Windows and notarization for macOS (remove first-launch security warnings)
• more high-quality ATS/company source adapters
• stronger quality gate tests
• clearer vector matching state in the UI
• contributor-friendly source plugin boundaries
• OS keychain support for API keys

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Legal & Privacy

JustHireMe is local-first: your profile, leads, and generated documents stay on your device. The full policies live in docs/legal/:

These policies govern use of the app and site; the source code is licensed separately under AGPL-3.0 (below). Governed by the laws of India; contact pls@justhireme.ai. See the legal index.

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License

JustHireMe is open source under the GNU Affero General Public License v3.0 only.

You may self-host, modify, and use JustHireMe, including with your own API keys, under the terms of the AGPL-3.0 license. If you modify JustHireMe and make it available over a network, the AGPL requires you to provide the corresponding source code for that modified version to users of the network service.

Commercial licenses are available for organizations that want to use JustHireMe outside the AGPL terms, including private forks, proprietary modifications, embedding, white-labeling, or managed deployments. See COMMERCIAL_LICENSE.md for the commercial path.

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Maintainer Note

This project is being built in the open because one person cannot cover every job source, every market, every ranking edge case, and every packaging path alone.

The goal is a useful local tool and a welcoming codebase where contributors can add sources, improve ranking, and help job seekers get better signal with less noise.