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Snapshot 1 · 2026-11-06T10:56:23Z · JavaScript · Apache-2.0
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fb3984fd687d1f7ced111a0eed95de94b4337731ce76e7ccc4c0459561532d14GitHub description at capture
Store every accomplishment. Tailor every application. Own your career data.
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# CareerOps Store every accomplishment. Tailor every application. Own your career data. [**Try the demo**](https://careerops.telivity.app) · [**Quick start**](#quick-start) If you are self-hosting, see the [self-host troubleshooting guide](docs/TROUBLESHOOTING.md). Local-first · Open source · User-authored evidence only · Apache 2.0  *Memory → Promote → Resume → Interview* One local-first app that replaces your resume builder, job tracker, interview notes, accomplishment journal, and offer spreadsheet—for engineers, PMs, designers, and anyone who wants a durable record of their work. --- ## How it works ### 1. Remember what you actually did Capture accomplishments while they’re fresh. Originals stay immutable; you promote what belongs on a resume when you’re ready.  ### 2. Run your job search Fill a kanban from public ATS boards (or add roles yourself). Triage, track stages, and keep the search in one place—not a spreadsheet.  ### 3. Tailor resumes from evidence Generate drafts from ranked, user-authored memory—not invented metrics. Edit, version, export, then you apply on the employer site.  ### 4. Prepare interviews Pull interview angles from the same story bank and evidence you already captured—no blank-page prep before every round.  ### 5. Compare offers Side-by-side comparison of terms you enter. Decide with structure, not scattered notes.  ### 6. Build your portfolio Promote work into projects and portfolio evidence from the same memory you use for resumes and interviews.  ```mermaid flowchart LR Work --> Capture --> Promote --> Tailor --> Interview --> Offer --> Work ``` Capture while you work. Promote into structured history. Tailor for a real JD. Prep interviews from the same facts. Compare offers. Start the next loop with memory already built. --- ## Why people switch **“I forgot what I shipped six months ago.”** CareerOps had already saved it—so the next resume and interview prep started from real work, not a blank page. **“I had seven resume versions in Google Drive.”** CareerOps generated them from one source of truth instead of another copy-paste doc. **“I was paying for three different job search tools.”** CareerOps replaced the tracker, the resume tool, and the notes dump with one local-first application. --- ## Why use CareerOps instead of Teal, Huntr, Simplify, or AI resume builders? | | CareerOps | Typical alternatives | |--|-----------|----------------------| | Data | Local-first; you own it | Cloud SaaS | | License | Apache 2.0 open source | Proprietary | | Evidence | User-authored only; AI rewrites, never invents | AI-generated claims common | | Between searches | Accomplishment history you keep | One-off document generation | | Scope | Memory, board, resumes, interviews, offers, portfolio | Multiple disconnected tools | You apply on the employer site. CareerOps does **not** auto-apply. After the workflow above, that’s the Career Operating System idea: the system you keep between searches so the next one starts with organized evidence—not a blank page. --- ## Quick Start ```bash npx @telivity/careerops init ``` ≈5 minutes. Done. Self-host, schema, deploy, and agent skill details: [docs/](docs/) · [CONTRIBUTING.md](CONTRIBUTING.md) · [web/README.md](web/README.md) · [web/SCHEMA.md](web/SCHEMA.md) --- ## Architecture & Engineering Technical depth lives in `docs/` — not on the critical path for starring or trying the product. | Topic | Doc | |-------|-----| | Architecture | [docs/ARCHITECTURE.md](docs/ARCHITECTURE.md) | | Security model | [SECURITY.md](SECURITY.md) · [supabase/README.md](supabase/README.md) | | Resume provenance | [docs/DOCTRINE_MEMORY.md](docs/DOCTRINE_MEMORY.md) | | Transactional promotion | [docs/DOCTRINE_MEMORY.md](docs/DOCTRINE_MEMORY.md#promotion--bidirectional) | | Database schema | [supabase/README.md](supabase/README.md) · [`supabase/schema.sql`](supabase/schema.sql) · [SPA cheat-sheet](web/SCHEMA.md) | | Plugin system | [docs/PLUGINS.md](docs/PLUGINS.md) | | AI architecture / skill | [docs/SKILL.md](docs/SKILL.md) · [docs/CHAINS.md](docs/CHAINS.md) | | Local-first design | [docs/LOCAL_FIRST.md](docs/LOCAL_FIRST.md) | | Privacy model | [docs/PRIVACY.md](docs/PRIVACY.md) | | Roadmap | [docs/ROADMAP.md](docs/ROADMAP.md) | <details> <summary>Repo map (optional)</summary> | Path | Purpose | |------|---------| | `web/` | Dashboard SPA | | `supabase/functions/` | Edge functions | | `supabase/schema.sql` | Tables + RLS | | `training/` | Optional train/eval *code* | | `.agents/skills/careerops/` | Open Agent Skill | | `packages/careerops` | `npx @telivity/careerops init` | </details> --- ## Contributing See [CONTRIBUTING.md](CONTRIBUTING.md). Community norms: [CODE_OF_CONDUCT.md](CODE_OF_CONDUCT.md). Releases: [CHANGELOG.md](CHANGELOG.md). --- ## License Copyright © Telivity and contributors. Licensed under the [Apache License, Version 2.0](LICENSE).