career-ops vs Hermes Agent
Two of the top projects in Assistants, side by side: who leads on each score part and who each one suits, then setup, license, activity and what each review found.
career-ops
Job-search agent that scores listings, tailors CVs and drafts applications
Hermes Agent
Self-hosted agent with skill learning, memory and Telegram/Discord/Slack gateway
Verdict
career-ops ranks higher, 95 to 87. Of the 4 score parts we measure for both, career-ops leads on 2, Hermes Agent on 1 and 1 is even.
- AdoptionHermes Agent leads by 3 points, 99 to 96: close to even.
- FreshnessEven at 100.
- Maintenancecareer-ops leads by 12 points, 93 to 81.
- Agent-readycareer-ops leads by 55 points, 85 to 30: a wide gap.
Pick career-ops if you are
Job seekers comfortable with a terminal and an AI coding CLI
- Drafts only: no auto-submit, and no mail transport in the code
- No telemetry or backend; CV goes only to the AI provider you choose
Pick Hermes Agent if you are
Self-hosters wanting a persistent personal agent reachable from chat apps
- One gateway process serves Telegram, Discord, Slack, WhatsApp, Signal and email with shared history
- Seven terminal backends, including Docker, SSH, Modal, Daytona and Vercel Sandbox
| What we compare | career-ops | Hermes Agent |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 96, widely used | 99, widely used |
| Freshness | 100, active | 100, active |
| Maintenance | 93, healthy | 81, healthy |
| Agent-ready | 85, ready | 30, minimal |
| Facts from GitHub and the README | ||
| Stars | 82.1k | 262.9k |
| License | MIT (permissive) | MIT (permissive) |
| Last commit | Nov 2026 | Nov 2026 |
| Last release | Nov 2026 | Nov 2026 |
| Language | JavaScript | Python |
| Docker | Yes | Yes |
| GPU | Not needed | Not needed |
| arm64 or Apple Silicon | Not stated | Mentioned |
career-ops
Runs inside an AI coding CLI (Claude Code, Codex, OpenCode, Qwen and others). You paste a job URL or description, and it checks the posting is live, scores fit against your CV, and generates an ATS PDF CV, cover letter and draft answers. It never submits applications or sends email, and keeps data on your machine.
Who it is for: Job seekers comfortable with a terminal and an AI coding CLI
Strengths
- Drafts only: no auto-submit, and no mail transport in the code
- No telemetry or backend; CV goes only to the AI provider you choose
- Covers evaluation, tailored PDF CV, cover letter, contact drafts, tracker and interview prep
- Portal scanner preconfigured for 100+ companies across Ashby, Greenhouse, Lever and Wellfound
Weaknesses
- Needs a separate AI CLI and provider; it does not run models itself
- README says early runs are rough until it learns your profile
- In-code check on CV rewording cannot catch every altered claim
- PDF output needs Playwright Chromium; non-Debian Linux needs manual libraries
- no GPU
- Docker + Compose
- Needs Node.js, An AI coding CLI (Claude Code, Codex, OpenCode, Qwen), Playwright Chromium (PDF generation)
- Models: Claude Code, Codex, OpenCode, Qwen, local models (see docs/RUNNING_ON_A_BUDGET.md)
Hermes Agent
Hermes Agent is a Python agent from Nous Research that runs from a terminal UI or a single gateway process serving Telegram, Discord, Slack, WhatsApp, Signal and email. It keeps persistent memory, creates and refines skills after complex tasks, searches past sessions with FTS5, and runs cron-scheduled jobs. Model providers are switchable with `hermes model`, and tools can run on seven backends including local, Docker, SSH and Modal.
Who it is for: Self-hosters wanting a persistent personal agent reachable from chat apps
Strengths
- One gateway process serves Telegram, Discord, Slack, WhatsApp, Signal and email with shared history
- Seven terminal backends, including Docker, SSH, Modal, Daytona and Vercel Sandbox
- Built-in cron scheduler, FTS5 session search and agent-created skills compatible with agentskills.io
- Works with Nous Portal, OpenRouter, OpenAI or any custom endpoint; MCP servers supported
Weaknesses
- Windows installer may trigger antivirus false positives on the bundled uv.exe
- Installs via a curl-piped shell script rather than a pinned package on desktop
- Skill self-improvement and user modeling behavior is described, but no benchmarks are given
- no GPU
- Docker + Compose
- Needs Python, Node.js, ripgrep, FFmpeg, Honcho (user modeling)
- Models: Nous Portal, OpenRouter, OpenAI, custom endpoints
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