提供了一个实用且组织良好的方法来构建具有分层内存和可复用技能的AI代理工作空间，特别适合现场演示和培训。
One app anchors every demo in the two-hour session. Meta-repo layout — start AI sessions at the repo root; that's where the hot memory and skills are auto-loaded:
Demo/ ← start AI sessions HERE (the workspace hub root)
├── AGENTS.md hot memory: constitution, routing, conventions
├── CLAUDE.md minimal pointer → AGENTS.md
├── mars.yaml catalog of project repos (multi-repo status/sync)
├── .claude/
│ └── skills/ implement-feature · route-to-flow · release-note
│ git-commit · git-open-pr · coding-convention
├── agent-hub/ the rest of the team brain
│ ├── knowledge-base/ cold memory: reference-spec · user-guide · decision-note
│ ├── flow-registry/ "what code implements this?"
│ └── tickets/ DEMO-101 (the Part 3 live-demo ticket)
├── taskflow-api/ FastAPI task tracker — homepage shows the session agenda
└── scan-simulator/ lightweight mock of the heavy external scan service
cd scan-simulator && pip install -r requirements.txt && uvicorn app.main:app --port 9000
cd taskflow-api && pip install -r requirements.txt && uvicorn app.main:app --port 8000
Open http://127.0.0.1:8000 — agenda + live task board.
| Session moment | What to do |
|---|---|
| Minute 0 | Open the homepage — agenda lives in the app |
| Part 2: contrast | Same request, plain prompt vs. agent started at repo root |
| Part 2: skills | Invoke release-note on recent tickets/commits |
| Part 3: memory layers | Walk the layers — AGENTS.md, .claude/skills/, agent-hub/knowledge-base/ |
| Part 3: force multipliers | route-to-flow on a question; show the simulator answering /v1/scan |
| Part 3: live pipeline | Run implement-feature on ticket DEMO-101, tests vs. simulator, board updates live |
根据分类、Topic 和编程语言匹配的相似项目。
Harness Engineering is a methodology for improving coding agent outputs by carefully crafting the environment around them—providing curated context, tools, and executable constraints that encode an organization’s nonfunctional requirements and cumulative lessons.
A 28.9 million parameter language model runs on an $8 ESP32-S3 microcontroller entirely on-device, generating simple stories at about 9.5 tokens per second.
mimic captures traffic from any iOS or web app and automatically generates a Python client library that lets you call the app's API like a regular library.