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A brief for an AI agent with tools

What for: brief an autonomous agent (web/code/files/MCP) so it doesn't wander: goal, tools, guardrails, definition of done.

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Building effective agents — Anthropic (tool design, простота) checked 2026-06-01

Updated: 02.07.2026

$ You are an autonomous agent. Achieve the GOAL below using the tools available…
A brief for an AI agent with tools

When to use it

You're launching an autonomous agent (Claude Code, the Cursor agent, an agent with MCP tools) that decides its own steps. Your role: the person setting the task. The result: a brief that tells the agent the goal, what to use, what NOT to do and when to stop — instead of an endless loop or a march in the wrong direction.

The prompt (copy and paste)

You are an autonomous agent. Achieve the GOAL below using the tools available.

GOAL (an outcome, not a process): "<FILL IN: what has to exist when you're done>".
TOOLS: <LIST: web search / code execution / files / DB (read-only) / specific MCPs> — and what each is for.
CONTEXT AND INPUTS: <links, file paths, project constraints>.

Working rules:
1. First write a short plan (3-6 steps) and show it, then act.
2. For facts and current data you MUST use tools, not memory. Never fabricate tool results.
3. GUARDRAILS: <NOT ALLOWED: changing or deleting data, spending money, writing outside these paths, anything irreversible without confirmation>.
4. If the task is ambiguous, make a reasonable assumption, RECORD it and carry on; stop and ask only at a genuine fork in the road.
5. Budget: no more than <N> steps/tool calls; if you run out, report what's blocking you.

DONE (how we'll know it's finished): <acceptance criteria — what to check>.
At the end, give a report: what you did, what you assumed, what didn't work.

Why it works: an agent needs a goal, guardrails and a done-criterion more than a step-by-step script — give it heuristics, not a rigid recipe; and keep the tool set narrow, or the agent won't know which one to call.

Filled-in example

Goal: "produce a comparison of 5 competitors as a table in competitors.md". Tools: web search (facts), files (write to ./research only). Guardrails: don't touch code outside ./research, don't publish. DONE: a table with price/features/audience columns plus source links.

How the AI should proceed: shows the plan (find the list → gather data on each → merge into a table → verify links), searches the web for each entry, records the assumption "using public pricing as of June 2026", writes the file into ./research, and lists in the report what it couldn't find.

Variations

  • Read-only recon. "Just gather and analyse, change NOTHING; propose a plan of changes for review" — for risky environments.
  • A narrow tool set. Give the agent 1-2 tools for a specific workflow rather than "everything" — accuracy goes up.
  • With a self-check. Add a step: "before reporting, reread DONE and verify each criterion yourself".

Pro tips

  • Phrase the GOAL as an outcome ("the table is built and verified"), not a process ("google it and write something") — that gives the agent a criterion for stopping.
  • A narrow tool set beats a wide one: if even a human couldn't say which tool fits a situation, the agent certainly will get it wrong. Don't wrap everything in sight.
  • Always set guardrails and a step budget: an autonomous agent with no "don'ts" and no iteration ceiling risks irreversible actions and infinite loops. Require confirmation before anything irreversible.

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