Home

Relevant source files

• .gitignore
• README.md
• docs/repo-map.md
• src-tauri/src/lib.rs
• src-tauri/src/main.rs
• src-tauri/tauri.conf.json

Lodestar is a local-first job-search workbench designed to manage the end-to-end lifecycle of job hunting through a structured, automated pipeline. It operates directly over a local Obsidian vault, treating plain-text Markdown files with YAML frontmatter as the primary source of truth for all entities (companies, jobs, and user profiles).

The system combines a high-performance Rust backend with a modern web frontend to provide deep automation—including web scraping, LLM-driven role analysis, and automated fit scoring—while maintaining the portability and longevity of local text files.

Architecture

Lodestar is built using Tauri v2, bridging a native Rust core with a SvelteKit frontend.

The Stack

• Backend (Rust): Handles file system I/O, the durable task queue (SQLite), LLM orchestration, and the job-fetch pipeline src-tauri/src/lib.rs#1-20
• Frontend (Svelte 5): Utilizes Runes for reactive state management and provides a multi-surface workspace for triaging roles and managing applications README.md#3-5
• Persistence: All domain data is stored in a user-selected Obsidian vault. The app also maintains a local data directory for its internal SQLite task queue src-tauri/src/lib.rs#30-33

System Relationship Diagram

This diagram illustrates how the frontend UI communicates with the Rust core to interact with the external environment and the local vault.

System Bridge: UI to Code Entities

flowchart TD
    subgraph subGraph3 ["Local Filesystem"]
        H["Obsidian Vault (*.md files)"]
        I["App Data (queue.db)"]
    end
    subgraph subGraph2 ["Backend (Rust Core)"]
        D["Note I/O (mod note)"]
        E["Pipeline Worker (mod worker)"]
        F["Task Queue (SqliteQueue)"]
        G["Watcher (mod watcher)"]
    end
    subgraph subGraph1 ["Tauri IPC Bridge"]
        C["Invoke Handlers (tauri::generate_handler!)"]
    end
    subgraph subGraph0 ["Frontend (SvelteKit + Runes)"]
        A["UI Surfaces (Companies, Jobs, Checks)"]
        B["Svelte Stores (companiesStore, checksStore)"]
    end
    A <--> B
    B --> C
    C --> D
    C --> E
    E --> F
    F --> I
    D <--> H
    G --> H
    G --> B

Loading

Sources: src-tauri/src/lib.rs#25-67README.md#3-5src-tauri/src/main.rs#4-6

Major Subsystems

1. Vault I/O & Note Primitives

The system treats Markdown files as structured objects. The note module is responsible for splitting files into YAML frontmatter and Markdown content, enabling round-trip writes that preserve user formatting while updating specific data fields.

• For details, see Note Primitives & Vault I/O.

2. The Job-Fetch Pipeline

A multi-stage automated engine that moves through discovery, detail extraction, and scoring. It uses ScrapingBee for resilient web scraping and OpenRouter for LLM-based analysis.

• Discovery: Scrapes career pages and structures listings.
• Detailing: Fetches full JDs and detects research gaps (e.g., missing salary or tech stack).
• Scoring: Compares job requirements against the user's TargetCriteria and Experience to produce a fit score.
• For details, see Job-Fetch Pipeline.

3. Fit Scoring Engine

A specialized Rust module (fit.rs) that calculates alignment across five dimensions: Seniority, Skills, Compensation, Arrangement, and Domain. It uses a "dealbreaker" logic where failure in a hard filter collapses the total score to zero.

• For details, see Fit Scoring Engine.

4. Product Surfaces

The UI is organized into several functional "surfaces" accessed via a rail navigation system.

Surface	Status	Purpose
Companies	Built	High-level view of targets, screening status, and active roles.
Checks	Built	Telemetry log for the pipeline; tracks LLM costs and scraping success.
Settings	Built	Configuration for API keys and vault pathing.
Triage	Planned	Focused, one-by-one review of new roles.
Pipeline	Planned	Kanban-style board for active applications.

• For details, see Product Surfaces & Navigation.

Core Data Flow

The following diagram maps the lifecycle of data from an external URL to a structured note in the local vault.

Data Flow: External URL to Code Entity

flowchart LR
    subgraph Persistence
        MD["Markdown + YAML"]
    end
    subgraph subGraph1 ["Pipeline (Rust Entities)"]
        SB["ScrapingBeeScraper"]
        OR["OpenRouterLlm"]
        JS["Job Struct"]
    end
    subgraph External
        URL["Job URL"]
    end
    URL --> SB
    SB --> OR
    OR --> JS
    JS --> MD

Loading

Sources: src-tauri/src/lib.rs#1-15README.md#7-18

Next Steps

• To set up your environment and API keys, see Getting Started & Configuration.
• To understand how to navigate the workspace, see Product Surfaces & Navigation.
• For a deep dive into the data structures, see The Vault: Data Model & Persistence.