career-ops

★ 77.9k

agent-afk

★ 62

career-ops vs agent-afk

Q: Which is better, career-ops or agent-afk?

By GitHub stars, career-ops has more community adoption, but the best choice depends on your specific use case.

career-ops: career-ops is a local-first job-search system that runs inside an AI coding CLI such as Claude Code, Codex, Qwen, OpenCode or Grok Build. Paste a job and it checks the posting is still live, scores it 1-5 against your real CV, and drafts an ATS-readable CV, cover letter, application answers and outreach notes. It never submits applications or sends email, has no telemetry, and keeps your data on your machine.; agent-afk: Agent AFK is an open-source, customizable coding agent harness designed for long-running development tasks, offering full control over its behavior, prompts, and tools. It allows users to run agents with various models, edit operational rules, and manage persistent memory across sessions.

TL;DR

career-opsWorkflow Automation · ★ 77.9k

Deciding which job postings are worth applying to

Read career-ops full review →

agent-afkWorkflow Automation · ★ 62

Automating lengthy coding projects: Delegate complex, multi-step coding tasks to run autonomously in the background.

Read agent-afk full review →

Side-by-Side Comparison

Field

career-ops

agent-afk

Features

career-ops

01A-H evaluation that scores a job against your CV and advises skipping weak fits

02Tailored ATS-readable CV PDFs and cover letters with an approval gate

03Portal scanner with 100+ preconfigured companies across Ashby, Greenhouse, Lever and Wellfound

04Interview prep, story bank, negotiation scripts and offer-stage contract review

05Terminal dashboard and pattern analysis of rejections and ghost-job reposts

agent-afk

01Customizable Agent Loop: Users can edit prompts, gates, routing, and skills, gaining full ownership and control over the agent's behavior.

02Headless Daemon Operation: Enables running long-duration coding tasks in the background, with optional notifications via Telegram upon task completion.

03Cross-Session Persistent Memory: Agents maintain preferences, decisions, and procedures across runs using both hot memory (for always-present facts) and a searchable fact archive.

04Built-in Task Orchestrators: Provides high-level commands like `/mint` for full feature development and `/diagnose` for automated bug root-cause analysis, dispatching waves of subagents.

05Multi-Surface Interaction: Supports interaction via one-shot commands, an interactive REPL, a headless daemon, and a Telegram bot, all sharing the same session manager and memory.

Use Cases

career-ops

↳Deciding which job postings are worth applying to

↳Tailoring CVs and cover letters per role without fabricating experience

↳Tracking an application pipeline and preparing for interviews

agent-afk

↳Automating lengthy coding projects: Delegate complex, multi-step coding tasks to run autonomously in the background.

↳Interactive terminal-based development: Use the REPL for real-time coding assistance, tool access, and plan mode, integrating directly into the developer's workflow.

↳Full feature development lifecycle: Orchestrate the entire process from idea (spec) to research, planning, building, verifying, and shipping new features using `/mint`.

↳Automated bug diagnosis and resolution: Employ `/diagnose` to automatically generate and test multiple root-cause hypotheses for failing tests or bugs.

↳Personalized agent knowledge management: Maintain and leverage a persistent memory of preferences, decisions, and procedures across all agent interactions.

Best For

career-ops

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career-ops vs agent-afk

TL;DR

Side-by-Side Comparison

Features

Use Cases

Best For

FAQ

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