hyperloop 0.19.0

Orchestrator that walks tasks through composable process pipelines using AI agents

hyperloop

Walks tasks through composable process pipelines using AI agents. You write specs, it creates tasks, implements them, verifies the work, and merges the results.

Prerequisites

• Python 3.12+
• kustomize (kustomize on PATH)
• git
• gh CLI (optional, for GitHub PR operations)
• An Anthropic API key, or Vertex AI / Bedrock credentials

Install

pip install hyperloop

Quickstart

mkdir my-project && cd my-project && git init && git commit --allow-empty -m init

# Write a spec
cat > specs/auth.md << 'EOF'
# User Authentication
Implement JWT-based auth. POST /auth/login, POST /auth/register, GET /auth/me.
Passwords hashed with bcrypt. JWTs expire after 24h.
EOF

# Initialize hyperloop structure
hyperloop init

# Run the orchestrator
export ANTHROPIC_API_KEY=your-key  # or CLAUDE_CODE_USE_VERTEX=1
hyperloop run

# With GitHub PR support
hyperloop run --repo owner/repo

How It Works

Agents run via the Claude Agent SDK — in-process, with full tool access (file I/O, git, shell). Each parallel worker gets its own git worktree for branch isolation. Serial agents (PM intake, process-improver) run on trunk.

The SDK handles tool execution, context management, and clean exit. No subprocess polling or result-file conventions.

Project Structure

After hyperloop init:

my-project/
├── .hyperloop.yaml                     # orchestrator config
├── .hyperloop/
│   ├── agents/
│   │   ├── kustomization.yaml          # composition point (base + process component)
│   │   └── process/
│   │       └── kustomization.yaml      # empty Component (process-improver writes here)
│   ├── state/
│   │   ├── tasks/                      # task metadata (YAML frontmatter)
│   │   └── reviews/                    # per-round review files
│   └── checks/                         # executable check scripts
└── specs/
    └── *.spec.md                       # product specs (your domain)

specs/ is yours — product specs only. .hyperloop/ is orchestrator-managed.

Prompt Composition

Three layers, all resolved via a single kustomize build:

Layer	Source	What it provides
Base	hyperloop repo base/	Core agent prompts
Project overlay	gitops repo or in-repo patches	Project-specific guidelines, persona
Process overlay	.hyperloop/agents/process/	Learned rules from process-improver

Agent resources have a guidelines field — additive by convention. At compose time: prompt + guidelines + spec + findings.

Configuration

# .hyperloop.yaml

overlay: .hyperloop/agents/             # path to kustomization dir
base_ref: github.com/org/hyperloop//base?ref=v1  # remote base for `hyperloop init`

target:
  repo: owner/repo                      # GitHub repo (omit for local-only)
  base_branch: main

runtime:
  max_workers: 6

merge:
  auto_merge: true
  strategy: squash
  delete_branch: true

poll_interval: 30
max_task_rounds: 50
max_cycles: 200
max_rebase_attempts: 3

observability:
  log_format: console                   # console | json
  log_level: info

  matrix:                               # optional
    homeserver: https://matrix.example.com
    registration_token_env: MATRIX_REG_TOKEN
    verbose: false

Custom Processes

Override the default pipeline (implement → verify → merge):

# process-patch.yaml
kind: Process
name: default
pipeline:
  - loop:
      - role: implementer
      - role: verifier
  - gate: human-pr-approval
  - action: merge-pr

Four primitives: role (spawn agent), gate (wait for signal), loop (retry on failure), action (terminal op). Loops nest.

Development

uv sync --all-extras
uv run pytest
uv run ruff check . && ruff format --check .
uv run pyright