← ClaudeAtlas

agent-craftlisted

Use when building, changing, debugging, evaluating or shipping an LLM agent or the harness around it (tool-calling loops, tool/function definitions, MCP servers, agent system prompts, context and memory handling, confirmation gates, multi-agent setups, agent evals and LLM judges). Also use when about to deploy an edited agent prompt, tool set or model, and when an agent misbehaves: it skips items, picks wrong tools, claims done without doing it, loops, stalls, or regresses. 开发/调试/评估 agent、智能体、function calling、harness,或改了 agent 的提示词/工具/模型准备上线时使用。
alextangson/harnessed · ★ 0 · AI & Automation · score 72
Install: claude install-skill alextangson/harnessed
# Agent Craft Why this exists (evidence, 2026-09). Without this skill, Claude already makes good calls on agent design. In baseline runs it: - pushed back on a LangGraph + RAG + mem0 stack; - put refund rules in code; - flagged prompt injection; - diagnosed before patching a prompt; - built an idempotent, fail-visible harness with 53 tests. What it did not do was make the agent's behavior verifiable from the start: - The build ended with model behavior "unverified: run it and read the replies". - Evals only appeared when a user pushed to ship, and then as a throwaway script. - In the author's production agent (2026-09), harness tests on scripted model replies stayed green while the live agent skipped batch items, narrated instead of acting, and fell back silently. So this skill does not re-teach judgment. It carries invariants from design into code, evals and traces, and it records lessons that only show up against real models. Incidents tagged [P] come from the author's production e-commerce agent. When you cite one, say where it comes from rather than presenting it as your own experience. ## Stance The model proposes; the harness decides. - Anything that must hold is enforced in code, with an error message that tells the model how to recover. That covers money, outbound messages, irreversible writes, batch completeness and budgets. - The prompt only steers quality. - Every harness component encodes an assumption about what the model can't do. Re-test those assumptions