How to Create Useful AI Agent Instruction Files

An instruction file is useful when it turns repository knowledge into actions an agent can follow: the command that proves a change, the directories it may edit, generated files it must avoid, and the example that represents the preferred pattern. File names may look interchangeable, but their loading rules are not. AGENTS.md, CLAUDE.md, Cursor project rules, and SKILL.md each have their own scope, activation, metadata, and precedence conventions.

Write for a new contributor who can inspect the code but cannot infer team habits. State observable requirements instead of personality wishes: `run pnpm test:api after changing src/api` is testable, while `be careful` is not. Keep universal rules near the repository root and narrow exceptions close to the files they govern when the client supports hierarchical instructions. Link to canonical examples instead of copying an entire style guide that will drift.

Choose the target client before drafting. Define scope, permitted objectives, protected paths, setup and verification commands, and the conditions that require human approval. Add concise examples for conventions that cannot be enforced by a formatter or test. For Cursor, select an activation model and provide `.mdc` front matter. For a skill, make the directory and `name` match, describe both what it does and when to use it, and move long resources into focused relative references.

The format rules come from the current OpenAI AGENTS.md, Claude Code memory, Cursor rules, and Agent Skills documentation. Where clients disagree, the selected client's documentation controls the file path, activation, and precedence advice.

Take one monorepo rule: changes under `src/api/**` must use the existing service pattern, must not edit `migrations/**`, and must pass `pnpm test:api`. In root AGENTS.md, describe the repository-wide rule and allow a nested file to add a narrower API exception. In CLAUDE.md, retain only guidance relevant to Claude Code's project memory. In a Cursor `.mdc` rule, set the glob to `src/api/**/*.ts`. In SKILL.md, use a name such as `api-change-review`, a trigger-focused description, and step-by-step validation instructions.

Effective guidance = applicable scope + unambiguous action + verification evidence. A long instruction with no activation rule or proof command is weaker than a short rule placed in the correct directory and backed by a test.

Precedence differs across clients, and two applicable files can conflict. Cursor ignores a plain `.md` file inside `.cursor/rules` because project rules require `.mdc` metadata. The Agent Skills specification limits names, requires them to match the parent directory, and marks `allowed-tools` experimental. Instructions can also become stale when scripts or paths change. Most importantly, prompt guidance is not authentication, authorization, sandboxing, or secret storage; enforce security with the platform and operating system.

Resolve blocking format errors, then review triggers, commands, file paths, scope, guardrails, token size, and testable verification steps. Watch for one recurring error: using vague advice, pasting secret values, omitting required skill metadata, or configuring an auto-attached Cursor rule without globs.

Select AGENTS.md, CLAUDE.md, Cursor rule, or SKILL.md, complete the scope and workflow fields, generate the draft, and read the validation findings. Correct metadata and vague commands before copying the file into its exact target path.

Input: target format, project context, scope, commands, constraints, examples, and format-specific metadata. Output: one copyable instruction file with local diagnostics and a suggested path. Generation does not install the file or prove that an agent obeys it.

Instruction content is edited locally and no model call is made. Guided fields produce a deterministic draft that remains fully editable with toolbar actions, undo and redo, live preview, expanded view, and protected manual changes.