Agent Orchestration Process (AOP)

AOP gives automation one CLI for controlling different agent harnesses without requiring callers to learn each harness's command flags, session format, output schema, runtime state, or resume behavior:

• Run Codex, Claude Code, Cursor Agent, Devin CLI, OpenCode, Antigravity (agy), Grok Build, Hermes, and DeepSeek Harness (dsh) through the same run and resume commands. See Harness adapters for current model support and limitations.
• Reuse each harness's existing authentication, model execution, tools, and conversations instead of maintaining a separate AOP credential store.
• Apply the same isolated worktrees, inputs-only sealed runs, configured deadlines, process cleanup, snapshotted inputs, and validated artifacts across harnesses.
• Retain consistent results, logs, timing, token usage, and exact provider session identity when available.
• Keep cleanup, checkpointing, and Git integration outside agent control.

Agent Client Protocol (ACP) standardizes interactive communication between agents and clients such as editors and IDEs. Use ACP when a person needs to chat, approve actions, watch progress, and steer a session.

Use AOP when software needs to run bounded jobs unattended across different agent CLIs. The two are complementary: ACP serves interactive clients, while AOP serves automation.

Install and run

AOP requires Linux and Python 3.11 or newer. The edit, review, and sealed profiles require bwrap. Git is required for edit, review, and host. Install and authenticate at least one supported agent harness.

Install AOP from PyPI:

uv tool install agent-orchestration-process

Run a sealed task from any directory without exposing local files or requiring a Git repository:

aop run --agent codex --profile sealed --prompt "Explain the difference between TCP and UDP"

Run a task in an existing Git repository:

aop init
aop run task-a --agent codex --prompt "Implement the parser and its tests"

aop init adds /.aop/ to .gitignore; commit that change before integrating tasks. AOP creates the task worktree automatically and prints the run ID needed to resume the exact provider session:

aop resume <run-id> --prompt "Address the review findings"

See the CLI guide for other harnesses, inputs, artifacts, batch runs, cleanup, and machine-readable results. See Integration when a task's changes are ready to checkpoint and merge.

Execution profiles

AOP profiles describe the complete execution boundary rather than only where writes are allowed. The isolated profiles expose only the declared workspace, inputs, provider runtime, private state, cache, scratch, output, and required operating-system paths. host runs without that isolation.

Inspect a declared profile or preview the intended policy without compiling or dispatching it:

aop profile explain sealed
aop profile explain sealed --agent codex --json
aop run study-arm --profile sealed --prompt "Answer using only declared inputs" --dry-run

All profiles currently retain native network connectivity because the supported provider CLIs need it. See Execution profiles for the exact filesystem, instruction, environment, credential, input, and output boundaries.

Results and usage

Every adapter records the same result shape, including provider session identity when available, timing, token usage, cost evidence, logs, and declared artifacts. See Token usage and pricing for the normalized token contract, provider mappings, and cost calculation rules.

Development

Clone the repository and synchronize its locked development environment:

git clone https://github.com/wakamex/agent-orchestration-process.git
cd agent-orchestration-process
uv --no-config sync --locked
uv --no-config run --locked pytest
uv --no-config run --locked ruff check src tests