Open source · MIT licensed

Screen smarter. Hire faster. Powered by AI.

SYJ TalentFlow CLI parses resumes, scores candidates against your job description, ranks them, and drafts interview kits and recruiter emails — from a single command, on any machine you already own.

Star on GitHub Download Documentation

Install in seconds

$ git clone github.com/SHalimoosavi/SYJ-TalentFlow-Cli.git && npm install

Windows Linux macOS Android · Termux

talentflow — zsh

Candidate	Score	Status
Fatima Siddiqui	79%	SHORTLISTED
Asha Verma	69%	REVIEW
Rahul Mehta	14%	REJECTED

3Parsed

1Shortlisted

1Review

54%Avg match

✔ Reports generated in ./output

Capabilities

Everything a screening pipeline needs, none of the bloat.

Nine focused capabilities, each usable on its own or chained into a full pipeline.

Resume parsing

Extracts name, contact, skills, experience, education, certifications, and projects from TXT and Markdown resumes into structured JSON.

AI resume matching

Combines keyword overlap, weighted skills/experience scoring, and optional AI semantic evaluation against your job description.

Candidate ranking

Classifies every candidate into Shortlisted, Review, or Rejected using configurable thresholds — exported as CSV, JSON, or Markdown.

Interview generator

Produces technical, behavioural, culture-fit, resume-specific, and follow-up questions for every shortlisted candidate.

Email generator

Drafts interview invitations, rejections, info requests, final-round invites, and offer prep in formal, friendly, startup, or corporate tone.

Beautiful CLI dashboard

ASCII banner, progress bars, status badges, and ranking tables — a terminal UI that reads like a real product, not a script.

Cross-platform

Identical behavior on Windows, Linux, macOS, and Android Termux, with zero native dependencies to break your install.

Open source

MIT-licensed on GitHub, with a documented architecture, test suite, and contribution guide — built to be forked and extended.

AI providers

Bring your own key: Anthropic, OpenAI, or OpenRouter, switchable with a single environment variable — never hardcoded.

See it in action

A dashboard that actually reads like one.

Real output from talentflow screen — candidate rankings, score bars, and status badges, rendered straight to your terminal.

SYJ TalentFlow CLI terminal dashboard showing a candidate ranking table with match scores, progress bars, status badges for Shortlisted, Review, and Rejected, and summary statistics including candidates parsed and average match percentage

Ranking table Sorted by match score

Progress bars Skill & experience fit

Status badges Shortlisted · Review · Rejected

Live statistics Parsed, average match, totals

Command line, perfected

Five commands. One pipeline.

Select a command to see exactly what it does.

talentflow doctor

$talentflow doctor

✔ Node.js version — v22.x (requires >=22)

✔ AI_PROVIDER value — anthropic

⚠ AI provider credentials — API key missing

✔ resumes directory — found

ℹ Environment looks good. Run "talentflow screen" to get started.

talentflow parse

$talentflow parse --resumes resumes/

→ Parsing resumes from resumes/

✔ Parsed asha-verma.txt

✔ Parsed fatima-siddiqui.txt

✔ Parsed rahul-mehta.md

ℹ Parsed 3 resume(s) → output/parsed

talentflow screen

$talentflow screen --jd jobs/backend.txt --resumes resumes/

→ Scoring candidates…

Candidate	Score	Status
Fatima Siddiqui	79%	SHORTLISTED
Asha Verma	69%	REVIEW

ℹ Reports written to output/

talentflow interview

$talentflow interview --jd jobs/backend.txt

✔ Interview kit written for Fatima Siddiqui → output/interviews/fatima-siddiqui.md

ℹ Generated 1 interview kit(s) → output/interviews

# Technical Questions

- Walk me through designing a system using Node.js at scale.

talentflow reports

$talentflow reports --jd jobs/backend.txt

✔ Reports regenerated:

output/report.md

output/report.json

output/report.csv

How it works

One pipeline, from resume to hire.

Each stage is a separate, testable module — business logic stays independent of the CLI layer.

Resume

TXT / Markdown input

Parser

Structured JSON

Scoring engine

Keyword + weighted

AI providers

Semantic scoring

Reports

MD / JSON / CSV

Recruiter

Decision + outreach

Bring your own AI

Pluggable by design.

Switch providers with one environment variable — no code changes required.

Anthropic

Claude models for semantic resume scoring and drafting.

Supported now

OpenAI

GPT models via the standard chat completions API.

Supported now

OpenRouter

Access many hosted models through a single API key.

Supported now

Ollama

Local model inference, no API key required.

Planned

LM Studio

Run local models with a friendly desktop UI.

Planned

⌂

Local LLM

Any OpenAI-compatible local inference server.

Planned

Why TalentFlow

Not another ATS subscription.

TalentFlow CLI trades a monthly invoice and a locked-in dashboard for a tool you own outright.

Traditional ATS platforms

Monthly per-seat subscription fees
Your resume data lives on their servers
Closed source, black-box scoring
Requires internet access, every time
Locked to one vendor's roadmap

TalentFlow CLI

Free forever — MIT licensed
Resumes stay on your own machine
Open source, fully auditable scoring logic
Runs fully offline in non-AI mode
Cross-platform: Windows, Linux, macOS, Termux

Open source, forever

Watch it grow on GitHub.

SHalimoosavi / SYJ-TalentFlow-Cli

AI-powered recruitment automation toolkit for the command line. Cross-platform, dependency-light, MIT licensed.

View repository

—Stars

—Forks

—Open issues

MITLicense

—Contributors

v1.0.0Latest release

Roadmap

What's next.

v1.1

Plugin-based document support

PDF pluginDOCX plugin

v1.5

Extensibility & integration

Plugin SDKREST API

v2.0

Beyond the terminal

Web dashboardAnalyticsEnterprise

FAQ

Questions, answered plainly.

What is SYJ TalentFlow CLI?

SYJ TalentFlow CLI is an open-source, MIT-licensed command-line toolkit that automates recruitment work: parsing resumes, matching them against a job description with AI, ranking candidates, and generating interview kits and recruiter emails.

Who is TalentFlow CLI for?

Recruiters, hiring managers, technical founders, and engineering teams who want to screen resumes quickly without adopting a heavyweight ATS platform, and who are comfortable working from a terminal.

How does TalentFlow CLI work?

Point it at a job description and a folder of resumes. It parses each resume into structured data, scores candidates using keyword, weighted, and optional AI semantic scoring, ranks them into Shortlisted, Review, and Rejected buckets, and writes Markdown, JSON, and CSV reports. From there you can generate interview kits and recruiter emails for shortlisted candidates.

What platforms are supported?

TalentFlow CLI runs on Windows, Linux, macOS, and Android via Termux. It has zero native dependencies, so installation is identical across every platform.

Is TalentFlow CLI open source?

Yes. TalentFlow CLI is fully open source under the MIT License, hosted on GitHub, and open to community contributions.

Does TalentFlow CLI support AI?

Yes. TalentFlow CLI supports Anthropic, OpenAI, and OpenRouter as pluggable AI providers for semantic resume scoring, interview question generation, and recruiter email drafting. Support for local models via Ollama and LM Studio is planned.

Can TalentFlow CLI work offline?

Yes. Every feature has a non-AI fallback. Resume parsing, keyword and weighted scoring, ranking, and Markdown/JSON/CSV reporting all run entirely locally without an internet connection or API key.

How do I install TalentFlow CLI?

Clone the GitHub repository, run npm install, then run the CLI with node bin/talentflow.js or link it globally with npm link. Requires Node.js 22 or newer.

What AI providers are supported?

TalentFlow CLI currently supports Anthropic, OpenAI, and OpenRouter through a shared AIProvider abstraction, switchable with a single environment variable.

How is TalentFlow CLI different from traditional ATS software?

Traditional ATS platforms are cloud-hosted, subscription-based, and often lock in your data. TalentFlow CLI is a local-first, open-source command-line tool with no vendor lock-in, no mandatory cloud dependency, and no license fee — you own your data and your workflow.