This guide is for planning AI agent workflows. Review security, privacy, legal, data retention, and human approval requirements before giving an agent tool access.
Agent specs reduce risk before the first tool call
An AI agent is more than a prompt. Once it can use tools, read files, call APIs, or take follow-up actions, you need clear boundaries. A strong spec separates what the agent may read, draft, recommend, change, and never execute without approval.
Goal and scope
State the job, success criteria, inputs, outputs, and what is deliberately out of scope.
Tool permissions
Separate capabilities from permissions: read, draft, modify, publish, delete, pay, message, or call external APIs.
Approval gates
Define which actions need human review before side effects happen in production systems.
Evaluation cases
Test complete input, missing context, risky actions, tool failure, conflicting instructions, and evidence gaps.
A practical AI agent spec workflow
1. Define the agent job
Write the task, user, input sources, expected output, and the decision the agent should help with.
2. Map allowed tools
List each tool, what data it can read, what actions it can take, and where human approval is required.
3. Add memory and privacy rules
Specify what can be remembered, what must stay session-only, and what should never be stored.
4. Write failure behavior
Tell the agent how to handle missing evidence, tool errors, permission gaps, high-risk data, and ambiguous instructions.
Draft an AI agent specification
Use the AI agent spec generator to turn an agent job, tool list, risk notes, and operating mode into a structured implementation brief.
Open agent spec generator常见问题
What is an AI agent specification?
It is a planning document that defines an agent goal, tools, permissions, workflow, memory rules, approval gates, failure handling, and evaluation cases.
Why write an agent spec before building?
It exposes risk, unclear permissions, missing approval gates, and data-flow decisions before they become harder to change in code.
What should an AI agent never do automatically?
High-impact actions such as publishing, deleting data, sending external messages, making payments, or changing production systems should normally require explicit approval.