Why design before coding an agent?

Agents fail in subtle ways — runaway loops, tool misuse, no escalation path. Designing the goal, memory, tools, guardrails, and evals first surfaces those risks on paper, where they are cheap to fix, instead of in production where they are expensive.

What memory types does it cover?

It distinguishes none (stateless), short-term (within a single task or conversation), and long-term (persisted across sessions, often via a vector store or database). The prompt asks the model to justify the choice and define what is stored and for how long.

How does it handle tool access?

You list each tool the agent may use; the prompt instructs the model to define inputs, outputs, side effects, and a least-privilege boundary for each, plus what happens when a tool call fails.

What are escalation paths?

Conditions under which the agent must stop and hand control to a human — low confidence, irreversible actions, repeated failures, or policy-sensitive decisions. The design doc makes these explicit so the agent is never fully unsupervised on high-stakes actions.

Does it cover evaluation?

Yes. The output design doc includes success criteria, failure modes to test, and the metrics you will track, so you can tell whether the agent actually works before and after launch.

AI Agent Design Planner

AI agent design planner

Most agent projects fail not at coding but at design: an unclear goal, unbounded tool access, no memory strategy, and no escalation path. This planner walks you through the decisions that matter — goal, memory, tools, guardrails, and evaluation — and turns them into a structured prompt that produces a complete agent design document you can review before writing any code.

How it works

You define the agent’s single primary goal, list the tools it may call, choose a memory model, set the output format, and specify when it must escalate to a human. The tool assembles a prompt that instructs an LLM to expand those choices into a full design doc: architecture overview, the control loop, tool contracts with least-privilege boundaries, memory schema, guardrails, escalation rules, and an evaluation plan. Everything is generated locally in your browser.

Tips and notes

One primary goal. Agents that chase several goals at once become unpredictable; scope to one and add others later as separate agents or tools.
Least privilege per tool. Define exactly what each tool can touch and what happens on failure — unbounded tool access is the most common agent risk.
Always have an escalation path. Irreversible or high-stakes actions should require human confirmation; the design doc forces you to name those triggers.
Plan evals first. Decide how you will measure success before building, or you will not know whether the agent works.