Free open source alternative app list about topic "cli" :

CodeWhale

CodeWhale is a free, open-source alternative to Claude Code . Codewhale Codewhale is an open source coding agent for your terminal, built in Rust and improved in public with the people who use it. 简体中文 · 日本語 · Tiếng Việt · Bahasa Indonesia · 한국어 · Español · Português · Русский · Українська · Français · Deutsch · 繁體中文 · हिन्दी · Türkçe · Italiano · Polski · العربية · Català Install npm install -g codewhale codewhale The first run helps you connect a provider or stay offline. Codewhale also supports Cargo, Docker, Nix, Scoop, prebuilt archives, Android/Termux, and a CNB mirror. See the installation guide . Use Talk to Codewhale the same way you would talk to a teammate: Fix the failing tests and explain what changed. Or run a task without opening the TUI: codewhale exec " fix the failing tests and explain what changed " Codewhale can read your repository, edit files, run commands, inspect results, and keep working toward a goal. You decide how much access it has. Why Codewhale Use the model you want. Connect hosted providers or local models through Ollama, vLLM, or SGLang. Switch provider and model with /model . Stay in control. Plan is read-only. Ask, Auto-Review, and Full Access make approval behavior visible. /undo reverts the last turn and /restore returns the workspace to an earlier snapshot. Keep long work organized. Save sessions, set a durable /goal , review workflows before they run, and coordinate agents without turning their internal instructions into your transcript. Extend the agent you already have. Connect MCP servers and skills, configure hooks, and keep agent roles as readable files in your project or personal settings. Run /help in the TUI for commands and keyboard shortcuts. Safety Codewhale runs on your machine with the access you grant it. Approval modes and repository rules limit what the agent may do; optional OS sandboxing adds a stronger execution boundary where supported. Unknown model prices stay unknown instead of being reported as free. Read authorization order for the exact policy stack and configuration for local settings. Documentation Providers and local models Agent teams MCP , hooks , and configuration Local web client All documentation Join the community Codewhale gets better when people use it, report what feels wrong, and help fix it. If a provider is missing, a workflow is awkward, or the terminal UI gets in your way, open an issue . If you know how to improve it, open a pull request . First contributions are welcome, and contributors keep credit for the work that lands. Join the Discord , or add Hunter on WeChat ( hunterbown ) and ask to join the Whale Brothers group. Project history Codewhale began as deepseek-tui and still preserves that configuration and session compatibility. It is now provider-neutral and independently maintained; it is not affiliated with any model provider. Thanks to every contributor and to the open source communities that helped the project grow. See the contributor record . License MIT

FreeWindowsmacOSLinux

career-ops

career-ops is a free, open-source alternative to Teal . English | Español | Deutsch | Français | Português (Brasil) | 한국어 | 日本語 | 简体中文 | 繁體中文 | Українська | Русский | Polski | Dansk | தமிழ் | العربية | हिन्दी | Türkçe I spent months applying to jobs the hard way. So I engineered the system I wish I had. Companies use AI to filter candidates. I just gave candidates AI to choose companies. Now it's open source. FEATURED IN 740+ job listings evaluated · 100+ personalized CVs · 1 dream role landed Also runs on any agent-skill-standard CLI. See Supported CLIs . What Is This career-ops ( career-ops.org , also known as careerops ) turns any AI coding CLI into a full job search command center. Instead of manually tracking applications in a spreadsheet, you get an AI-powered pipeline that: Evaluates offers with a structured evaluation -- blocks A-F scored across 5 weighted dimensions, plus block G, a separate posting-legitimacy assessment that never affects the 1-5 score Generates tailored PDFs -- ATS-optimized CVs customized per job description Scans portals automatically (Greenhouse, Ashby, Lever, company pages) Processes in batch -- evaluate 10+ offers in parallel with sub-agents Tracks everything in a single source of truth with integrity checks Researches companies and finds the right person to contact -- applications get you in the queue; research gets you a conversation Important: This is NOT a spray-and-pray tool. career-ops is a filter -- it helps you find the few offers worth your time out of hundreds. The system strongly recommends against applying to anything scoring below 4.0/5. Your time is valuable, and so is the recruiter's. Always review before submitting. career-ops is agentic: whichever AI coding CLI you choose navigates career pages with Playwright, evaluates fit by reasoning about your CV vs the job description (not keyword matching), and adapts your resume per listing. Heads up: the first evaluations won't be great. The system doesn't know you yet. Feed it context -- your CV, your career story, your proof points, your preferences, what you're good at, what you want to avoid. The more you nurture it, the better it gets. Think of it as onboarding a new recruiter: the first week they need to learn about you, then they become invaluable. Built by someone who used it to evaluate 740+ job offers, generate 100+ tailored CVs, and land a Head of Applied AI role. Read the full case study . The CareerOps Manifesto career-ops is the first reference implementation of the CareerOps Manifesto . read it. if it says what you believe, sign it. your signature becomes a commit. Features Feature Description Auto-Pipeline Paste a URL, get a full evaluation + PDF + tracker entry A-G Evaluation Role summary, CV match, level strategy, comp research, personalization, interview prep (STAR+R) -- plus a Block G posting-legitimacy check that flags scams and ghost jobs, and a Work-Auth signal that flags an explicit no-sponsorship JD as a hard blocker Interview Story Bank Accumulates STAR+Reflection stories across evaluations -- 5-10 master stories that answer any behavioral question Negotiation Scripts Salary negotiation frameworks, geographic discount pushback, competing offer leverage ATS PDF Generation Keyword-injected CVs with Space Grotesk + DM Sans design Cover Letter Generator Research-backed cover letters with keyword mirroring, four interactive angle prompts (why/problems/approach/tone), draft-in-chat approval gate, and A4 PDF via the same HTML + Playwright pipeline as CVs. Auto-drafts on every evaluation; complete and generate on demand via /career-ops cover Application Email Drafts Formal recruiter/referral/cold application emails from a report or pasted JD, with subject line, attachment checklist, source-backed fit points, and a profile-driven contact block. Draft-only -- career-ops never sends, submits, or clicks anything. Portal Scanner 100+ companies pre-configured (Anthropic, OpenAI, ElevenLabs, Retool, n8n...) + custom queries across Ashby, Greenhouse, Lever, Wellfound Funded Company Discovery Review-first company:funded command surfaces recently funded companies and source diagnostics from structured public feeds without editing your data Batch Processing Parallel evaluation with headless CLI workers ( claude -p / opencode run ) Dashboard TUI Terminal UI to browse, filter, and sort your pipeline Human-in-the-Loop AI evaluates and recommends, you decide and act. The system never submits an application -- you always have the final call Pipeline Integrity Automated merge, dedup, status normalization, health checks Interview Suite Time-blocked prep plans, practice sessions with feedback, post-interview debriefs ( interview/ ), and a company red-flag detector ( interview-redflag ) Offer Stage Contract reading companion -- clause walk plus a lawyer question list ( offer-prep ) -- and a desired/advertised/actual salary-gap analyzer ( salary-gap.mjs ) Follow-ups & Replies Follow-up cadence calculator and seeded reminders ( followup-cadence.mjs , followup-seed.mjs ); employer reply classification into tracker updates ( reply-watch ) Pattern Analysis Rejection patterns and per-ATS-channel advance rates ( analyze-patterns.mjs ), lifetime funnel stats ( stats.mjs ), repost/ghost-job detection ( detect-reposts.mjs ) Plugin System Opt-in integrations (Gmail, Notion, Apify + a community registry), disabled by default -- see docs/PLUGINS.md Beyond the CV Company research ( deep ) surfaces AI strategy, recent moves, engineering culture, and the angle your profile should take. Contact discovery ( contacto ) identifies the hiring manager, recruiter, or team peer worth reaching out to and drafts a ≤300-character LinkedIn message tuned to each contact type. Formal application email drafts ( email ) turn an evaluated report or pasted JD into a subject line, body, and attachment checklist without sending, submitting, or clicking anything. Applications get you in the queue; research gets you a conversation. Quick Start Fastest way — one command: npx @santifer/career-ops init 💡 npx ships with Node.js — it runs the installer once, without installing anything globally. No Node yet? Install it first. (Already using a Claude Code / Gemini / Codex CLI? Then you already have it.) This clones the latest release into ./career-ops and installs dependencies. Then: cd career-ops claude # or codex / qwen / opencode / agy / grok — open your AI CLI here On first launch, career-ops walks you through setup — your CV, profile and target roles — just by chatting. Nothing to edit by hand. Prefer to set it up manually? (git clone) git clone https://github.com/santifer/career-ops.git cd career-ops && npm install npx playwright install chromium # only needed for PDF generation # 2. Check setup npm run doctor # Validates all prerequisites # 3. Configure cp config/profile.example.yml config/profile.yml # Edit with your details cp templates/portals.example.yml portals.yml # Customize companies # 4. Add your CV # Create cv.md in the project root with your CV in markdown # 5. Open your AI CLI in this directory claude # or codex / opencode / qwen / agy / grok # Then ask your CLI to adapt the system to you: # "Change the archetypes to backend engineering roles" # "Translate the modes to English" # "Add these 5 companies to portals.yml" # "Update my profile with this CV I'm pasting" # 6. Start using # Paste a job URL or JD text to trigger auto-pipeline # If your CLI supports slash commands, use /career-ops (or its CLI-specific alias) # In Codex, ask for the same mode in plain language, e.g.: # "Run the career-ops scan mode" # "Run the career-ops pipeline mode for data/pipeline.md" # "Run the career-ops pdf mode for the latest evaluated role" # "Run the career-ops tracker mode and summarize the current statuses" Global install npm i -g @santifer/career-ops This installs the career-ops binary globally so you can run it directly instead of via npx . Unlike npx @santifer/career-ops init (which bootstraps a project directory), the global install gives you a persistent career-ops command available anywhere in your terminal. Which one should you use? npx @santifer/career-ops init — best for first use; creates a dedicated project folder. npm i -g @santifer/career-ops — best once you have a project folder and want to run career-ops commands directly. The system is designed to be customized by your AI coding CLI itself. Modes, archetypes, scoring weights, negotiation scripts -- just ask it to change them. It reads the same files it uses, so it knows exactly what to edit. See docs/SETUP.md for the full setup guide, docs/RUNNING_ON_A_BUDGET.md for instructions on running career-ops cheaply using custom or local models (and docs/FREE_TIER.md for running it at zero cost on Antigravity CLI's free tier), docs/AUTOMATION.md for scheduling recurring scans and a zero-token triage-to-shortlist recipe, docs/APPLY_AUTOFILL.md for details on the ATS auto-fill flow, and docs/FAQ.md for answers to common setup questions. Design principles live in ARCHITECTURE.md ; runtime flows in docs/ARCHITECTURE.md . Antigravity CLI Integration career-ops supports Antigravity CLI natively, the same way it supports Claude Code and OpenCode. All slash commands are available through the shared skill entrypoint, using the same modes/*.md evaluation logic. Google has transitioned consumer Gemini CLI access to Antigravity CLI. GEMINI.md is now a no-op compatibility guard so Antigravity does not duplicate the full project instructions when it reads both AGENTS.md and GEMINI.md . Native Antigravity CLI # 1. Run in the career-ops directory cd career-ops agy # 2. Use the unified /career-ops command with subcommands: /career-ops " Senior AI Engineer at Anthropic... " /career-ops pipeline /career-ops scan /career-ops pdf /career-ops tracker The skill is defined using the open standard in .agents/skills/career-ops/SKILL.md and symlinked/referenced for each supported CLI (e.g. .claude/ , .cursor/ , .qwen/ , .antigravitycli/ , .grok/ ). Codex Integration career-ops supports Codex through the same shared router, but the invocation model is different from CLIs that auto-register slash commands. For the full guide, see docs/CODEX.md . Interactive Codex cd career-ops codex Slash commands are not guaranteed in Codex. If /career-ops is unavailable, ask Codex to run the mode directly in plain language: Evaluate this JD with career-ops auto-pipeline: https://company.com/jobs/123 Run the career-ops scan mode and summarize new matches. Run the career-ops pipeline mode for data/pipeline.md. Run the career-ops pdf mode for the latest evaluated role. Run the career-ops tracker mode and summarize the current statuses. One-shot Codex ( codex exec ) codex exec " Evaluate this JD with career-ops auto-pipeline: https://company.com/jobs/123 " codex exec " Run career-ops scan mode in this repo and summarize new matches. " codex exec " Run career-ops pipeline mode for data/pipeline.md. " codex exec " Run career-ops pdf mode for the latest evaluated role. " codex exec " Run career-ops tracker mode and summarize the current statuses. " Grok Build CLI Integration career-ops supports Grok Build CLI natively, the same way it supports Claude Code and OpenCode. AGENTS.md is auto-loaded as project rules, and all slash commands are available through the shared skill entrypoint. Native Grok Build CLI # 1. Run in the career-ops directory cd career-ops grok # 2. Use the unified /career-ops command with subcommands: /career-ops " Senior AI Engineer at Anthropic... " /career-ops pipeline /career-ops scan /career-ops pdf /career-ops tracker For headless batch workers, use grok -p "prompt" (add --yolo to auto-approve tool executions). Standalone Gemini API Script (No CLI install needed) # 1. Get a free API key at https://aistudio.google.com/apikey cp .env.example .env # Edit .env, set GEMINI_API_KEY=your_key_here # 2. Install dependencies npm install # 3. Evaluate a job description node gemini-eval.mjs " We are looking for a Senior AI Engineer... " node gemini-eval.mjs --file ./jds/my-job.txt node agent-inbox.mjs add " ... " # queue a request for the next session npm run gemini:eval -- " JD text here " Free tier: Both options work without billing. Native CLI uses Google OAuth; the API script uses gemini-3.6-flash (rate limits are model- and tier-dependent; see Google AI docs for current quotas). Usage career-ops uses a shared command router. In CLIs that register slash commands, it looks like this: /career-ops → Show all available commands /career-ops {paste a JD} → Full auto-pipeline (evaluate + PDF + tracker) /career-ops scan → Scan portals for new offers /career-ops pdf → Generate ATS-optimized CV /career-ops cover → Cover letter generator (paste JD or /career-ops cover {slug}) /career-ops email → Formal application email draft (draft-only; never sends, submits, or clicks) /career-ops batch → Batch evaluate multiple offers /career-ops tracker → View application status /career-ops apply → Fill application forms with AI /career-ops outcome → Record application outcome & archive artifacts /career-ops pipeline → Process pending URLs /career-ops contacto → Find hiring manager / recruiter / peer + draft a ≤300-char LinkedIn message per contact type /career-ops deep → Generate a structured 6-axis research prompt (AI strategy, recent moves, culture, challenges, competitors, candidate angle) /career-ops training → Evaluate a course/cert /career-ops project → Evaluate a portfolio project Or just paste a job URL or description directly -- career-ops auto-detects it and runs the full pipeline. In Codex, slash commands are not guaranteed. Use the same mode names in a prompt instead, or call them from codex exec . How It Works You paste a job URL or description │ ▼ ┌──────────────────┐ │ Archetype │ Classifies: LLMOps / Agentic / PM / SA / FDE / Transformation │ Detection │ └────────┬─────────┘ │ ┌────────▼─────────┐ │ A-G Evaluation │ Match, gaps, comp research, STAR stories, legitimacy │ (reads cv.md) │ └────────┬─────────┘ │ ┌────┼────┐ ▼ ▼ ▼ Report PDF Tracker .md .pdf entry Pre-configured Portals The scanner comes with 100+ companies ready to scan and 45+ search queries across major job boards. Copy templates/portals.example.yml to portals.yml and add your own: AI Labs: Anthropic, OpenAI, Mistral, Cohere, LangChain, Pinecone Voice AI: ElevenLabs, PolyAI, Parloa, Hume AI, Deepgram, Vapi, Bland AI AI Platforms: Retool, Airtable, Vercel, Temporal, Glean, Arize AI Contact Center: Ada, LivePerson, Sierra, Decagon, Talkdesk, Genesys Enterprise: Salesforce, Twilio, Gong, Dialpad LLMOps: Langfuse, Weights & Biases, Lindy, Cognigy, Speechmatics Automation: n8n, Zapier, Make.com European: Factorial, Attio, Tinybird, Clarity AI, Travelperk Job boards searched: 55+ provider modules cover ATS APIs, board-wide feeds, XML/RSS feeds, markdown feeds, and local parsers. See Supported job boards for the full table. By default node scan.mjs (a.k.a. npm run scan ) trusts what each ATS feed returns. Some companies leave stale postings in their public API even after the role is closed, so those expired entries can leak into pipeline.md . Pass --verify to launch Playwright after the API pass and drop expired postings before they hit the pipeline: node scan.mjs --verify # zero-token discovery + Playwright liveness check The verification is sequential and only runs against new offers (after dedup), so the cost stays bounded. Dashboard TUI The built-in terminal dashboard lets you browse your pipeline visually: npm run serve:dashboard # launch the TUI npm run build:dashboard # optional: build the standalone binary Features: 6 filter tabs, 4 sort modes, grouped/flat view, lazy-loaded previews, inline status changes. There is also an experimental web UI (alpha, opt-in — nothing runs unless you start it): see web/README.md . Project Structure career-ops/ ├── AGENTS.md # Canonical agent instructions (all CLIs) ├── CLAUDE.md # Claude Code wrapper (imports AGENTS.md) ├── CODEX.md # Codex wrapper (imports AGENTS.md) ├── OPENCODE.md # OpenCode wrapper (imports AGENTS.md) ├── GEMINI.md # Legacy no-op guard to avoid Antigravity duplicate context ├── cv.md # Your CV (create this) ├── article-digest.md # Your proof points (optional) ├── config/ │ └── profile.example.yml # Template for your profile ├── modes/ # Skill modes │ ├── _shared.md # Shared context (customize this) │ ├── oferta.md # Single evaluation │ ├── pdf.md # PDF generation │ ├── cover.md # Cover letter generation │ ├── email.md # Formal application email drafts │ ├── scan.md # Portal scanner │ ├── batch.md # Batch processing │ └── ... ├── templates/ │ ├── cv-template.html # ATS-optimized CV template │ ├── portals.example.yml # Scanner config template │ └── states.yml # Canonical statuses ├── batch/ │ ├── batch-prompt.md # Self-contained worker prompt │ └── batch-runner.sh # Orchestrator script ├── dashboard/ # Go TUI pipeline viewer ├── data/ # Your tracking data (gitignored) ├── reports/ # Evaluation reports (gitignored) ├── output/ # Generated PDFs (gitignored) ├── fonts/ # Space Grotesk + DM Sans ├── docs/ # Setup, customization, budget guide, architecture └── examples/ # Sample CV, report, proof points Tech Stack Agent : AI coding CLI with shared skills and modes ( AGENTS.md + CLI wrapper) PDF : Playwright + HTML template Cover letters : HTML template + Playwright (A4 PDF, same pipeline as CVs) Scanner : Playwright + Greenhouse API + WebSearch Dashboard : Go + Bubble Tea + Lipgloss (Catppuccin Mocha theme) Data : Markdown tables + YAML config + TSV batch files Also Open Source cv-santiago -- The portfolio website (santifer.io) with AI chatbot, LLMOps dashboard, and case studies. If you need a portfolio to showcase alongside your job search, fork it and make it yours. FAQ What is career-ops? career-ops is an open-source, CLI-agnostic job-search command center. It turns any AI coding CLI into a pipeline that evaluates job offers against your CV, generates ATS-tailored PDFs, finds the right person to contact, and tracks everything in one place — while you keep the final decision. It is the first reference implementation of the CareerOps Manifesto. More at career-ops.org . Can I run career-ops for free, or on a cheaper / local model? Yes. career-ops is CLI-agnostic and runs on free and local models — via OpenRouter free models, Ollama, or any OpenAI-compatible endpoint — so you are not tied to a paid subscription. See docs/RUNNING_ON_A_BUDGET.md for the full setup. I pay for Claude Pro/Max but career-ops is burning API credits. Why? Because an ANTHROPIC_API_KEY in your environment takes precedence over your logged-in subscription: the CLI uses the key and bills per token. Run echo $ANTHROPIC_API_KEY , and if it prints anything, remove it from your shell profile, restart the terminal and run /login . Batch mode is the exception, since claude -p workers do not use the interactive login: run claude setup-token once and export the result as CLAUDE_CODE_OAUTH_TOKEN . Full walkthrough in docs/RUNNING_ON_A_BUDGET.md . Which AI CLIs does career-ops work with? career-ops runs on any major AI coding CLI — Claude Code, Codex, Gemini / Antigravity, OpenCode, Grok, Qwen and more — through the open Agent Skill Standard, so it is never locked to a single vendor. Use the CLI you already have. How do I install career-ops on Windows? career-ops runs on Windows. If skills fail to load with a symlink error during install, the fix is in docs/FAQ.md . Full steps are in docs/SETUP.md . Does career-ops auto-apply to jobs for me? No. career-ops is a filter, not a spray-and-pray auto-applier. The AI evaluates, ranks and drafts; you review and decide. It never submits, sends, or clicks anything — you always have the final call. That human-in-the-loop design is the whole point. Is career-ops free and open source? Yes. career-ops is free and open source, and for the candidate it always will be — it is the first reference implementation of the CareerOps Manifesto . Read it, and if it says what you believe, sign it. About the Author I'm Santiago Fernández de Valderrama Aparicio (santifer) -- Head of Applied AI, former founder (built and sold a business that still runs with my name on it). I built career-ops to manage my own job search. It worked: I used it to land my current role. Curious how this repo is maintained in ~4 hours a week? Read Agentic maintenance: how career-ops is run by a fleet of AI agents . My portfolio and other open source projects → santifer.io Wikidata: Santiago Fernández de Valderrama Aparicio · career-ops . Disclaimer career-ops is a local, open-source tool, NOT a hosted service. By using this software, you acknowledge: You control your data. Your CV, contact info, and personal data stay on your machine and are sent directly to the AI provider you choose (Anthropic, OpenAI, etc.). We do not collect, store, or have access to any of your data. You control the AI. The default prompts instruct the AI not to auto-submit applications, but AI models can behave unpredictably. If you modify the prompts or use different models, you do so at your own risk. Always review AI-generated content for accuracy before submitting. You comply with third-party ToS. You must use this tool in accordance with the Terms of Service of the career portals you interact with (Greenhouse, Lever, Workday, LinkedIn, etc.). Do not use this tool to spam employers or overwhelm ATS systems. No guarantees. Evaluations are recommendations, not truth. AI models may hallucinate skills or experience. The authors are not liable for employment outcomes, rejected applications, account restrictions, or any other consequences. See LEGAL_DISCLAIMER.md for full details. This software is provided under the MIT License "as is", without warranty of any kind. Contributors Every person who has shipped code, docs, translations or tests is listed in CONTRIBUTORS.md — including non-code contributions, which the graph above cannot show. Got hired using career-ops? Share your story! License & Trademark The code is licensed under MIT . The "career-ops" name and brand are governed by the Trademark Policy , permissive for community use, reserved for commercial product naming and endorsement. Let's Connect

FreeWindowsmacOSLinux

maigret

maigret is a free, open-source alternative to Pipl . Maigret English · 简体中文 Maigret collects a dossier on a person by username only , checking for accounts on a huge number of sites and gathering all the available information from web pages. No API keys required. AI profiling (demo) . Sponsors IPcook provides reliable residential proxies for online research, username discovery, and public data collection workflows. High success rates • 99.99% uptime • Response time under 0.5s • Monthly & Pay-as-you-go • Non-expiring traffic • Up to 10 free sub-accounts for team collaboration • Residential proxies from $0.3–$3.2/GB. Special Offer : FREE 100MB trial available. Use code WELCOME20 for 20% off. RapidProxy provides high-performance residential proxies for Twitter scraping, Selenium automation, and web data extraction. 90M+ IPs • Smart rotation • Anti-block • Non-expiring traffic. Special Offer : Try it free — Plans from $0.65/GB. Use code RAPID10 for 10% off. Contents In one minute Main features Demo Installation Usage Contributing Commercial Use About In one minute Ensure you have Python 3.10 or higher. pip install maigret maigret YOUR_USERNAME No install? Try the community Telegram bot or a Cloud Shell . Want a web UI? See how to launch it . See also: Quick start . Main features Supports 3,000+ sites ( see full list ). A default run checks the 500 highest-ranked sites by traffic; pass -a to scan everything, or --tags to narrow by category/country. Embeddable in Python projects — import maigret and run searches programmatically (see library usage ). Extracts all available information about the account owner from profile pages and site APIs, including links to other accounts. Performs recursive search using discovered usernames and other IDs. Allows filtering by tags (site categories, countries). Detects and partially bypasses blocks, censorship, and CAPTCHA. Fetches an auto-updated site database from GitHub each run (once per 24 hours), and falls back to the built-in database if offline. Works with Tor and I2P websites; able to check domains. Ships with a web interface for browsing results as a graph and downloading reports in every format from a single page. Optional AI analysis mode ( --ai ) that turns raw findings into a short investigation summary using an OpenAI-compatible API. For the complete feature list, see the features documentation . Used by Professional OSINT and social-media analysis tools built on Maigret: Demo Video Reports PDF report , HTML report Full console output Installation Already ran the In one minute steps? You're set. Below are alternative methods. Don't want to install anything? Use the community Telegram bot . Windows Download maigret_standalone.exe from Releases . You can launch it two ways: Double-click it — Maigret will ask for a username, run a default search, and wait at the end so the report links stay visible. Run it from a terminal — open Command Prompt (press Win+R , type cmd , hit Enter) or PowerShell to pass extra options: cd %USERPROFILE% \Downloads maigret_standalone.exe USERNAME maigret_standalone.exe USERNAME --html :: also save an HTML report maigret_standalone.exe --help :: list all options Video guide: https://youtu.be/qIgwTZOmMmM . Cloud Shells Run Maigret in the browser via cloud shells or Jupyter notebooks: Local installation (pip) # install from pypi pip3 install maigret # usage maigret username From source # or clone and install manually git clone https://github.com/soxoj/maigret && cd maigret # build and install pip3 install . # usage maigret username Docker Two image variants are published: soxoj/maigret:latest — CLI mode (default) soxoj/maigret:web — auto-launches the web interface # official image (CLI) docker pull soxoj/maigret # CLI usage docker run -v /mydir:/app/reports soxoj/maigret:latest username --html # Web UI (open http://localhost:5000) docker run -p 5000:5000 soxoj/maigret:web # Web UI on a custom port docker run -e PORT=8080 -p 8080:8080 soxoj/maigret:web # manual build docker build -t maigret . # CLI image (default target) docker build --target web -t maigret-web . # Web UI image Troubleshooting Build errors? See the troubleshooting guide . PDF reports ( --pdf ) are an optional extra — install with pip install 'maigret[pdf]' . They need system-level graphics libraries on Linux/macOS; see the PDF reports section for per-OS install steps. Usage Examples # make HTML, PDF, and XMind reports maigret user --html maigret user --pdf maigret user --xmind # legacy XML with a manifest for XMind 2022+ readers # machine-readable exports maigret user --json ndjson # newline-delimited JSON (also: --json simple) maigret user --csv maigret user --txt maigret user --graph # interactive D3 graph (HTML) maigret user --neo4j # Neo4j Cypher script (graph database) # search on sites marked with tags photo & dating maigret user --tags photo,dating # search on sites marked with tag us maigret user --tags us # highlight sites whose page also mentions specific keywords maigret user --keywords python rust # keyword-matched sites are shown with "[++]" in bright green # search for three usernames on all available sites maigret user1 user2 user3 -a # AI-assisted investigation summary (needs OPENAI_API_KEY) maigret user --ai --neo4j writes a *_neo4j.cypher script of the results graph; import it with cypher-shell -u neo4j -p <password> < report_user_neo4j.cypher or paste it into the Neo4j Browser. Re-imports are idempotent. See the Neo4j export docs . Run maigret --help for all options. Docs: CLI options , more examples . Running into 403s or timeouts? See TROUBLESHOOTING.md . Web interface Maigret has a built-in web UI with a results graph and downloadable reports. Don't want to run it yourself? Deploy the published soxoj/maigret:web Docker image as a hosted app in one click: Runs on Render's free tier (spins down after 15 min idle, spins back up on the next request). No login is set up on the instance, so anyone with the URL can use it. Web Interface Screenshots maigret --web 5000 Open http://127.0.0.1:5000 , enter a username, and view results. Python library Maigret can be embedded in your own Python projects. The CLI is a thin wrapper around an async function you can call directly — build custom pipelines, feed results into your own tooling, or run it inside a larger OSINT workflow. See the full library usage guide for a working example, async patterns, and how to filter sites by tag. Useful CLI flags --parse URL — parse a profile page, extract IDs/usernames, and use them to kick off a recursive search. --permute — generate likely username variants from two or more inputs (e.g. john doe → johndoe , j.doe , …) and search for all of them. --self-check [--auto-disable] — verify usernameClaimed / usernameUnclaimed pairs against live sites for maintainers auditing the database. --ai / --ai-model — run the AI analysis over the search results and stream a short investigation summary to the terminal. AI analysis --ai collects the search results, builds an internal Markdown report, and sends it to an OpenAI-compatible chat completion endpoint to produce a short, neutral investigation summary (likely real name, location, occupation, interests, languages, confidence, follow-up leads). Per-site progress is suppressed and the model's output is streamed to stdout. export OPENAI_API_KEY=sk-... maigret user --ai # pick a different model maigret user --ai --ai-model gpt-4o-mini The key can also be set as openai_api_key in settings.json . The endpoint defaults to https://api.openai.com/v1 , but openai_api_base_url in settings.json can point to any OpenAI-compatible API (Azure OpenAI, OpenRouter, a local server, …). See the settings docs for the full list of options. Tor / I2P / proxies Maigret can route checks through a proxy, Tor, or I2P — useful for .onion / .i2p sites and for bypassing WAFs that block datacenter IPs. # any HTTP/SOCKS proxy maigret user --proxy socks5://127.0.0.1:1080 # Tor (default gateway socks5://127.0.0.1:9050) maigret user --tor-proxy socks5://127.0.0.1:9050 # I2P (default gateway http://127.0.0.1:4444) maigret user --i2p-proxy http://127.0.0.1:4444 Start your Tor / I2P daemon before running the command — Maigret does not manage these gateways. Cloudflare bypass Experimental. The Cloudflare webgate is under active development; the configuration schema, CLI behaviour, and the set of routed sites may change without backwards-compatibility guarantees. A subset of sites in the database require a real browser to solve a JavaScript challenge. Maigret can offload these checks to a local FlareSolverr instance: docker run -d -p 8191:8191 --name flaresolverr ghcr.io/flaresolverr/flaresolverr:latest maigret --cloudflare-bypass < username > The bypass is opt-in ( --cloudflare-bypass or cloudflare_bypass.enabled in settings.json ) and only fires for sites whose protection field matches. See the feature docs for backend options and configuration. Contributing Add or fix new sites surgically in data.json (no json.load / json.dump ), then run ./utils/update_site_data.py to regenerate sites.md and the database metadata, and open a pull request. For more details, see the CONTRIBUTING guide and development docs . Release history: CHANGELOG.md . Commercial Use The open-source Maigret is MIT-licensed and free for commercial use without restriction — but site checks break over time and need active maintenance. For serious commercial use — with a daily-updated site database or a username-check API — reach out: 📧 [email protected] Private site database — 5 000+ sites, updated daily (separate from the public open-source database) Username check API — integrate Maigret into your product About Disclaimer For educational and lawful purposes only. You are responsible for complying with all applicable laws (GDPR, CCPA, etc.) in your jurisdiction. The authors bear no responsibility for misuse. Feedback Open an issue · GitHub Discussions · Telegram SOWEL classification OSINT techniques used: SOTL-2.2. Search For Accounts On Other Platforms SOTL-6.1. Check Logins Reuse To Find Another Account SOTL-6.2. Check Nicknames Reuse To Find Another Account License MIT © Maigret

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continue

continue is a free, open-source alternative to GitHub Copilot . Continue Pioneering open-source coding agent What is Continue? Note: The continuedev/continue repository is no longer actively maintained and is read-only for all users. Continue is a coding agent available as a CLI , VS Code extension , and JetBrains plugin . Documentation To learn how to configure Continue, how it works, and how to customize it, check out the Continue Docs . Final 2.0.0 Release We polished Continue and did a final 2.0.0 release of the VS Code extension, CLI, and JetBrains plugin. This included removing anonymous telemetry, pulling out authentication, squashing bugs, and more. VS Code CLI JetBrains Note: We recommend using the Continue CLI instead of the JetBrains plugin. Contributors Thank you to the entire Continue community for helping us create a pioneering coding agent. What we built together pushed the boundaries of what AI developer tooling could be. We hope this codebase continues to serve as a foundation for others. Code friends License Apache 2.0 © 2023-2026 Continue Dev, Inc.

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