Routines and Headless

Sat, 03 Oct 2026 00:00:00 +0000

Note

TL;DR

Routines are the default for repeat work. They run on Anthropic’s infrastructure with nothing for you to host.
Headless mode with -p is for when the job needs your pipeline and you want to pipe data through a script.
--bare is for when CI needs the same results every single run.
The Agent SDK is for when the work belongs inside your own product.

Routines

A routine is the most direct way to automate a task. There’s no script and no server.

It bundles:

a prompt
the repository it works on
any connectors it needs
a schedule

Then it runs that bundle in the cloud whenever it’s triggered.

The infrastructure is Anthropic’s (i.e., in the cloud). There’s no machine of yours staying on overnight, and there’s no workflow file for you to maintain. You describe the job once and it just runs.

A routine can fire on a few kinds of triggers:

A cron schedule, like every morning at 9am.
An HTTP POST to its API endpoint, so your own code can kick it off.
A GitHub event, like a new pull request landing.

-> Anything that’s the same prompt on a recurring trigger is a good fit

Creating a Routine

Two ways to create a routine:

Create one from the web at claude.ai/code/routines. You give it a name, write the instructions describing what Claude should do in each session, pick a repository, and choose a trigger.
create one from inside Claude Code: Run the /schedule command and describe what you want in plain language

Example:
```
/schedule daily dependency audit at 9am
```

Three Things to Know Before You Rely on Routines

Before you lean on routines for anything important, keep these three limits in mind:

Routines are a research preview.

Behavior and limits will keep moving, so don’t be surprised if things change.
A recurring schedule runs at most hourly.

If you need something more frequent, routines aren’t the tool.
Runs start from a fresh clone of your default branch, push to claude/ branches freely, and get checked before pushing anywhere else.

Headless Mode

Sometimes the job needs your environment, or logic wrapped around the run. That’s when you drop to headless mode.

“Headless” means running without the interactive interface (the “head”).

Normally you open Claude Code, type prompts, watch it work, and approve things.
In headless mode you run one command, Claude does the job, prints the result to standard output, and exits (Just like executing a shell command).

The -p flag (short for --print) turns it on: It runs Claude Code as a one-shot command with no interactive UI. It reads standard in and writes standard out, so it pipes like any other shell tool.

Example:

claude -p "summarize the changes in this diff"

Caution

-p skips auto-discovery of hooks, skills, plugins, MCP servers, and the CLAUDE.md file. You get Claude plus the tools you allow explicitly, and nothing the local environment happens to load.

Interactive example: Interactive vs. headless Claude Code

Getting structured output back

When using headless mode, you can pair a JSON schema with the JSON output format, and Claude will constrain its output to match your schema. The object that matches your schema lands in the structured_output field of the JSON response.

Example:

claude -p "Extract the exported function names from src/core/style.js" \
 --output-format json \
 --json-schema '{"type":"object","properties":{"functions":{"type":"array","items":{"type":"string"}}},"required":["functions"]}' \
 | jq '.structured_output.functions'

When to use and not use headless

When to use headless

You need your own environment. For example, the job needs local data, GPUs, or internal tools that a cloud routine can’t reach.
You want to pipe data through a script. For example: git diff | claude -p "review this" | tee review.md.
You need structured output. Pair --output-format json with --json-schema and read structured_output in your code.
You’re batch-processing. Loop over files or tickets and call claude -p once per item.
You’re running in CI. Add --bare when you need the same results every run.
You want multi-step automation. Capture the session_id from the JSON, then claude --resume it in a later step (plan first, execute later).

When not to use headless

Exploring or debugging something you don’t understand yet. Use the interactive mode, where you can steer.
A simple recurring prompt on a repo (e.g. a morning dependency audit). A routine is simpler, and you host nothing.
Work that belongs inside your product. That’s what the Agent SDK is for.

Multi-Step Automation with Sessions

For work that happens across multiple steps, you don’t have to cram everything into one command. Capture the session’s ID from the JSON output and resume it later:

claude --resume "$(jq -r .session_id /tmp/plan.json)"

One script kicks off the work. Another resumes it later with full context. This is handy when the first pass produces a plan and a second pass carries it out.

Deterministic Runs for CI

When CI needs the same results every single run, use the --bare flag, which gives you deterministic mode.

It’s the right choice when you’re running Claude Code inside a pipeline and you want repeatable, predictable output rather than anything that varies run to run.

The Agent SDK

The Agent SDK gets you a library that embeds Claude Code inside your own TypeScript or Python applications.

Both languages expose a query function and the same primitives as the CLI. You pass a prompt plus options, like:

allowedTools to control what Claude can do,
a system prompt,
and a permission mode.

Then you iterate over the messages Claude streams back and handle them however your app needs. It’s the same engine as the CLI, just callable from inside your product.

GitHub Actions and Code Review

Sat, 03 Oct 2026 00:00:00 +0000

GitHub Actions and Code Review

Automate Repeat Work |

Routines and Headless

TL;DR

Routines

Creating a Routine

Three Things to Know Before You Rely on Routines

Headless Mode

Getting structured output back

When to use and not use headless

Multi-Step Automation with Sessions

Deterministic Runs for CI

The Agent SDK

GitHub Actions and Code Review