research/harness-engineering/index.md
hermes c978db1437 Restructure agent research under agent-infra umbrella
- Add agent-infra umbrella topic (hub for state, harness, model-access, collaboration lenses)
- Split harness-engineering out of durable-agent-runtime; fold in Cloudflare Code Mode finding
- Narrow durable-agent-runtime to state/durability lens; retitle
- Tag codex-app-server-byo-auth as agent-infra subtopic
- Document umbrella-topic convention in README
2026-08-11 08:16:18 +00:00

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title: Harness Engineering — Agent Loops & Code-as-Tool-Interface description: The agent harness layer — how the agent loop is built and how the model interacts with tools. Covers nanocodex (agent as in-process library), pi minimalism, Codex protocols, and code-as-tool-interface (Cloudflare Code Mode: tools as typed API, progressive discovery, V8 sandbox). status: active category: technical tags: [harness, agent-loop, code-as-tool, codemode, cloudflare, nanocodex, pi, codex, tool-calling, typed-events, agent-infra] draft: true created: 2026-08-11 updated: 2026-08-11 origin: buzz://d8a718be-031f-4a6e-9f5c-a55466641654/c66f017974f748bd6db019c913d3a6f59de349e0cbd90ae38c222e9640521d63

Harness Engineering — Agent Loops & Code-as-Tool-Interface

Summary

The harness is the layer that runs the agent loop: it connects the model to tools, manages context, and streams events. Split out of durable-agent-runtime (2026-08-11) because it is a distinct lens — durability is about state; harness engineering is about the loop and the tool interface. Central 2026 finding: code-as-tool-interface — the harness should look like a programming environment, not a tool-call menu.

Key Findings

  • Code as the tool interface is the converging pattern (three independent sources):
    • Cloudflare Code Mode: MCP tools become a generated TypeScript API; the model writes code that calls it
    • nanocodex: typed Turn/TurnResult events over WebSocket beat stdout parsing
    • Prime Agent RLM: a persistent IPython REPL is the model's only tool
  • Why code beats direct tool calls: LLMs are trained on real code, not synthetic tool-call tokens; intermediate results don't pollute context; composed logic is reusable.
  • Cloudflare Code Mode mechanics (see analysis): tools as typed methods, progressive discovery (codemode.search() / codemode.describe()), execution safety via V8 isolate, six integration surfaces, experimental status.
  • Minimalism wins for small harnesses: pi's 4-tool philosophy; don't load a huge MCP catalog into context.

Sources

Primary: https://developers.cloudflare.com/agents/tools/codemode/ (2026-08-11); https://learn.chatgpt.com/docs/app-server; nanocodex repo; Prime Agent RLM (arXiv 2605.09998). See durable-agent-runtime/sources for shared references.

Detail Files

Next Steps

  • Prototype the "Code Mode pattern for Effect TS": expose our MCP/REST tools as a typed API agents write code against
  • Evaluate which harness primitives (typed events, streaming items, code sandbox) belong in our own agent tooling