Agent tools foundation · Module · 中文版
The agent tool landscape (optional)
Foundation path module 0 — orientation across six agentic coding tools; pick the one that fits your environment and observe its evidence habits.
Agent tools foundation · Module · 中文版
Foundation path module 0 — orientation across six agentic coding tools; pick the one that fits your environment and observe its evidence habits.
Points: 10 · Type: orientation · Evidence: self-attested
Before the hands-on courses, get your bearings: what the tools are, what they have in common, and which one you will drive first.
Six agentic coding tools carry this path’s hands-on courses. Pick by where you want to work:
| Tool | Where it runs | What it’s good at |
|---|---|---|
| Claude Code | terminal | long multi-step tasks, strong instruction following, reads CLAUDE.md/AGENTS.md |
| Codex (desktop app) | desktop app | task threads with approvals and diff review, reads AGENTS.md |
| Cursor | IDE | Agent/Ask/Plan modes inside an editor, .cursor/rules project rules |
| DeepSeek Harness | Python framework | plugin-composed agents (cordis.yml), auditable append-only trajectories |
| Kimi Code | terminal | built-in explore/plan/coder subagents that split reading, planning, editing |
| ZCode | desktop app | long-horizon Goal Mode, task lists, workspace Git state, remote check-ins |
They differ in interface, not in fundamentals. Every one of them: reads your files, follows written instructions, edits code, runs commands, and — this is the important part — can be wrong in ways that look right. That is why this path spends so much effort on rules and verification, not on prompts.
Choosing by environment: live in the terminal → Claude Code or Kimi Code. Live in a GUI → Codex app, Cursor, or ZCode. Want to assemble and audit the agent loop itself → DeepSeek Harness. You only need one to start; the route challenge at the end asks for a second, different one.
You have finished this module when you can answer, in your own words:
Self-attested checkpoint: when you can answer both, record it — module M0 of the Foundation path is worth 10 points. Honest self-reporting is the rule of this platform: nobody checks your answer, but nothing here is a certificate.
Record
Your agent fetches the path folder the same way as courses — one sentence starts the track on its course pages. Claim codes print from python verify.py in the path folder.
Paste the code your run printed on the progress page — an account keeps the points and the badge progress.
An authorized agent submits module codes in the same batch as course checkpoints — nothing to copy by hand.