HireKit

Research companies. Match jobs. Ace interviews.

An open-source CLI that turns 4-8 hours of company research into a single command. Pulls data from 8 sources, builds a weighted scorecard, and preps you for the interview โ€” all in your terminal.

$ pip install hirekit
8
Data Sources
12
Report Sections
100pt
Scorecard System
0
Tracking / Privacy

Everything you need to land the job

Six commands that cover the entire job application lifecycle โ€” from first research to final offer.

๐Ÿ”
hirekit analyze

Company Analysis

Deep-dive into any company. Pulls financials from DART, news from 6 sources, GitHub tech maturity, and culture signals โ€” assembled into a 12-section structured report.

๐ŸŽฏ
hirekit match

JD Matching

Paste a job description and get a fit score. Identifies skill gaps, highlights strengths, and suggests which projects to lead with in your application.

๐Ÿ—ฃ๏ธ
hirekit interview

Interview Prep

Generates company-specific interview questions based on real data โ€” tech stack, recent news, business challenges. Know what's coming before you walk in.

๐Ÿ“„
hirekit resume

Resume Review

Scores your resume against the target role. Gives actionable feedback on keyword alignment, impact statements, and ATS optimization.

โœ‰๏ธ
hirekit coverletter

Cover Letter

Drafts a tailored cover letter using real company context. References specific business challenges, products, and values โ€” not a generic template.

๐Ÿ”Œ
hirekit sources

Plugin System

List and manage data source plugins. Add custom sources with a 20-line Python interface โ€” @SourceRegistry.register and you're live.

๐Ÿค–
LLM-Optional
Works without AI. Enhanced with OpenAI / Anthropic / Ollama.
๐Ÿ”’
Privacy-First
All data stays local. No telemetry, no external tracking.
โšก
Parallel Collection
8 sources collected concurrently. Minutes, not hours.

8 Data Sources, Zero Gaps

From regulatory filings to AI-powered semantic search โ€” every angle covered.

๐Ÿ“Š DART KR

Official financial filings, employee headcount, salary data from Korea's regulatory database.

DART_API_KEY
๐ŸŸข Naver News KR

Recent Korean news articles, blog posts, cafรฉ discussions โ€” culture and interview intel.

NAVER_CLIENT_ID
๐Ÿ™ GitHub Global

Tech maturity scoring โ€” repo activity, stack diversity, open-source culture signal.

gh CLI
๐Ÿ“ฐ Google News Global

RSS-based global news feed. No API key required โ€” free out of the box.

No key needed
๐ŸŒ Credible News Global

Reuters, Bloomberg, FT, WSJ + major Korean business press aggregated and ranked.

No key needed
๐Ÿฆ Brave Search Global

Independent web + news semantic search. Privacy-respecting alternative to Google.

BRAVE_API_KEY
๐Ÿ”ฎ Exa Search Global

AI-powered semantic deep search. Surfaces hidden context and niche insights about companies.

EXA_API_KEY
โž• Your Source

Build a custom plugin with @SourceRegistry.register and 20 lines of Python.

Contribute a source โ†’

See It in Action

One command. Comprehensive scorecard. No guesswork.

zsh โ€” hirekit analyze
โฏ hirekit analyze ์นด์นด์˜ค --no-llm -o terminal

โ•ญโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€ HireKit Analysis โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ•ฎ
โ”‚ Analyzing: ์นด์นด์˜ค                                         โ”‚
โ”‚ Region: kr  Tier: 1  LLM: off                             โ”‚
โ•ฐโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ•ฏ

  Collecting from 8 sources in parallel...
  โœ“ DART financials          123ms
  โœ“ Naver News (32 articles)  210ms
  โœ“ GitHub tech scoring       380ms
  โœ“ Google News RSS           195ms
  โœ“ Credible News             290ms
  โœ“ Brave Search              445ms
  โœ“ Exa semantic search       512ms
  โœ“ Glassdoor reviews         340ms

  15 results collected across 8 sources in 512ms

                     ์นด์นด์˜ค Scorecard
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚ Dimension           โ”‚ Weight โ”‚  Score โ”‚ Evidence             โ”‚
โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค
โ”‚ Job Fit             โ”‚    30% โ”‚  3.5/5 โ”‚ Tech stack data      โ”‚
โ”‚ Career Leverage     โ”‚    20% โ”‚  4.6/5 โ”‚ 15 data points       โ”‚
โ”‚ Growth Potential    โ”‚    20% โ”‚  4.5/5 โ”‚ Financials + news    โ”‚
โ”‚ Compensation        โ”‚    15% โ”‚  3.5/5 โ”‚ DART salary data     โ”‚
โ”‚ Culture Fit         โ”‚    15% โ”‚  4.5/5 โ”‚ Reviews + Exa        โ”‚
โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค
โ”‚ Total               โ”‚        โ”‚  82/100 โ”‚ Grade S              โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜

  Report saved โ†’ ./reports/์นด์นด์˜ค_analysis.md

8 data sources ยท 15 results ยท collected in parallel ยท no LLM required

Quick Start

Three steps from zero to a full company report.

1

Install HireKit

Python 3.11+ required. Installs in seconds via pip.

# Standard install
$ pip install hirekit

# With LLM support (pick one)
$ pip install "hirekit[openai]"     # OpenAI
$ pip install "hirekit[anthropic]"  # Claude
$ pip install "hirekit[ollama]"     # Local models
2

Configure API Keys

Run the interactive setup wizard. DART + GitHub are enough to get started โ€” others are optional enhancements.

$ hirekit configure

# Config saved to ~/.hirekit/config.toml
# Or edit it directly:

[sources]
enabled = ["dart", "github", "naver_news"]

[llm]
provider = "none"  # or "openai", "anthropic", "ollama"
3

Run Your First Analysis

Analyze any Korean or global company. Results in your terminal or saved as Markdown.

# Analyze a company
$ hirekit analyze ์นด์นด์˜ค

# Match against a job description
$ hirekit match --jd job.txt --company kakao

# Prepare for the interview
$ hirekit interview ์นด์นด์˜ค

# View all available sources
$ hirekit sources

Roadmap

Where we've been and where we're going.

Phase 1 โ€” Complete

Foundation

  • โœ“ DART financial filings integration
  • โœ“ GitHub tech maturity scoring
  • โœ“ Multi-source news collection
  • โœ“ 5-dimension weighted scorecard (100pt)
  • โœ“ Structured Markdown reports (12 sections)
Phase 2 โ€” Complete

Job Application Suite

  • โœ“ JD matching with skill gap analysis (hirekit match)
  • โœ“ Company-specific interview prep (hirekit interview)
  • โœ“ Resume review and scoring (hirekit resume)
  • โœ“ Tailored cover letter generation
Phase 3 โ€” In Progress

Scale & Community

  • โ—ฆ US companies via SEC Edgar integration
  • โ—ฆ Web UI for non-CLI users
  • โ—ฆ Community plugin marketplace
  • โ—ฆ PyPI stable release

Built for the open-source community

HireKit is open source and welcomes contributions. Whether you want to add a new data source, improve report templates, or extend i18n support โ€” your work helps every job seeker.