# Show HN: Local automation runner with built-in LLM steps – YAML pipelines

> Source: <https://rorlikowski.github.io/stepyard/>
> Published: 2026-06-20 09:21:46+00:00

# Stepyard[¶](#stepyard)

**YAML pipelines. Python plugins. Runs on your machine - no server to set up, no cloud account needed.**

Stepyard is an automation runner for developers. Pipelines live as YAML files in your repo. You extend them with plain Python functions. Everything runs from the CLI or a local daemon - on your machine or a server you own.

```
pip install stepyard
stepyard init my-project && cd my-project
stepyard run hello
```

A deploy pipeline: build and push a container, run a smoke test, and post the result to Slack. One YAML file, no supporting scripts.

```
name: deploy
description: Build, push, and verify the production container.

steps:
  - id: build
    uses: shell.run
    with:
      command: docker build -t myapp:${{ env.GIT_SHA }} .

  - id: push
    uses: shell.run
    with:
      command: docker push myapp:${{ env.GIT_SHA }}

  - id: smoke_test
    uses: http.request
    with:
      url: https://staging.myapp.com/healthz
      method: GET

  - id: notify
    uses: llm.generate               # built-in - no plugin needed
    with:
      model: gpt-4o-mini
      prompt: |
        Summarise this deploy result in one sentence for Slack:
        HTTP status: ${{ steps.smoke_test.output.status }}
        SHA: ${{ env.GIT_SHA }}

  - id: post_to_slack
    uses: http.request
    with:
      url: ${{ env.SLACK_WEBHOOK }}
      method: POST
      json_body:
        text: ${{ steps.notify.output.output }}
```

Run it:

```
GIT_SHA=$(git rev-parse --short HEAD) stepyard run deploy
✓  build          12.4 s
✓  push            4.1 s
✓  smoke_test      0.3 s
✓  notify          0.9 s
✓  post_to_slack   0.2 s

Flow completed in 18.0 s
```

## Why Stepyard?[¶](#why-stepyard)

-
**Flows are files in your repo** Steps, conditions, loops, and retries are plain YAML keys - no proprietary DSL. Version-control them alongside your code and validate them with

`stepyard validate`

. -
**Extend with plain Python** One

`@node`

decorator turns any function into a reusable step. Inputs are type-validated automatically; plugin dependencies are isolated so they never conflict with Stepyard's own. -
**Nothing leaves your machine** State is stored in a local SQLite database. Data goes out only if a step in your flow explicitly sends it.

-
**Scheduled and on-demand execution**`cron`

,`interval`

, and`startup`

triggers. Run`stepyard service start`

and your flows execute on schedule - no external service or cloud account needed.

## Real-world examples[¶](#real-world-examples)

### Daily database backup[¶](#daily-database-backup)

```
name: pg_backup
trigger:
  uses: cron
  with:
    schedule: "0 3 * * *"   # every day at 03:00

steps:
  - id: dump
    uses: shell.run
    with:
      command: pg_dump ${{ env.DATABASE_URL }} | gzip > /tmp/backup.sql.gz

  - id: upload
    uses: shell.run
    with:
      command: |
        aws s3 cp /tmp/backup.sql.gz \
          s3://${{ env.BACKUP_BUCKET }}/db/$(date +%Y-%m-%d).sql.gz

  - id: cleanup
    uses: shell.run
    with:
      command: rm -f /tmp/backup.sql.gz
```

### Automated code review on every PR[¶](#automated-code-review-on-every-pr)

Fetch the diff via the GitHub API, review it with an LLM, and post a comment back - all with built-in nodes, no additional service.

```
name: pr_review
description: Review a PR diff with an LLM and post a comment if issues are found.
# Run: PR=42 GITHUB_REPO=my-org/my-repo stepyard run pr_review

steps:
  - id: diff
    uses: http.request
    with:
      url: https://api.github.com/repos/${{ env.GITHUB_REPO }}/pulls/${{ env.PR }}/files
      headers:
        Authorization: Bearer ${{ env.GITHUB_TOKEN }}
        Accept: application/vnd.github+json

  - id: review
    uses: llm.generate
    with:
      model: gpt-4o
      system_prompt: |
        You are a senior engineer doing a code review.
        Be concise. If everything looks good reply with exactly: LGTM
      prompt: |
        Review this pull request for bugs, security issues, and obvious mistakes:

        ${{ steps.diff.output.body }}

  - id: post_comment
    if: ${{ steps.review.output.output != "LGTM" }}
    uses: http.request
    with:
      url: https://api.github.com/repos/${{ env.GITHUB_REPO }}/issues/${{ env.PR }}/comments
      method: POST
      headers:
        Authorization: Bearer ${{ env.GITHUB_TOKEN }}
        Accept: application/vnd.github+json
      json_body:
        body: ${{ steps.review.output.output }}
```

### Multi-environment deployment with rollback[¶](#multi-environment-deployment-with-rollback)

```
name: deploy_multi

steps:
  - id: deploy_staging
    uses: shell.run
    with:
      command: kubectl apply -f k8s/staging/

  - id: integration_tests
    uses: shell.run
    continue_on_error: true
    with:
      command: pytest tests/integration/ -q

  - id: deploy_production
    if: ${{ steps.integration_tests.output.code == 0 }}
    uses: shell.run
    with:
      command: kubectl apply -f k8s/production/

  - id: rollback
    if: ${{ steps.integration_tests.output.code != 0 }}
    uses: shell.run
    with:
      command: kubectl rollout undo deployment/myapp -n staging
```

## Documentation overview[¶](#documentation-overview)

| Section | What you'll find |
|---|---|
|

[Core Concepts](concepts/)[How-to Guides](how-to/)[Built-in Nodes](nodes/builtin/)[Plugin Development](plugins/creating/)[CLI Reference](cli/reference/)## Compatibility[¶](#compatibility)

| Python | 3.10 · 3.11 · 3.12 · 3.13 |
| OS | macOS · Linux · Windows (WSL) |
| Storage | SQLite (default) |
| License | MIT |