agent6 0.0.2

Opinionated, sandboxed Python coding agent.

agent6

A sandboxed coding agent for Anthropic Claude and OpenAI-compatible backends (OpenAI, OpenRouter, Ollama, vLLM, LM Studio, llama.cpp). Linux-only.

• LLM calls are wrapped in deterministic Python workflows with a fixed tool surface.
• Every child process runs inside agent6-jail (Rust + Linux user namespaces + Landlock + seccomp).
• Git operations refuse push, --force, and history rewrite.
• No web UI, no plugin system, no telemetry, no auto-update.

Status: pre-release, version 0.0.1. 208 tests pass. The synthetic benchmark in bench/results.md surfaced four reproducible workflow issues that should land before a tagged 0.1.0 PyPI release.

Threat model

The worker model is treated as adversarial. It must not be able to:

• write outside the project's working directory
• read files outside the project (plus any sibling read-only paths)
• reach the network except the host:port of each [providers.*] block (when sandbox.network = "provider_only")
• rewrite, push, or hard-reset git history
• leave background processes running after the run ends

Enforcement is layered:

• Landlock is applied to the agent's own Python process to restrict what it can read/write.
• agent6-jail (a small Rust binary) wraps every child command: fresh user/mount/pid/ipc/uts/net namespace, pivots into a minimal rootfs, applies Landlock and a seccomp filter, drops capabilities, then execs the child.

See SECURITY.md for the per-layer breakdown.

Architecture

                     ┌───────────────────────────────────┐
                     │           agent6 CLI              │
                     └───────────────┬───────────────────┘
                                     │
                ┌────────────────────┼────────────────────┐
                │                    │                    │
        ┌───────▼───────┐  ┌─────────▼─────────┐  ┌──────▼──────┐
        │  workflows/   │  │      agents/      │  │   graph/    │
        │   implement   │  │   planner, worker │  │   curator   │
        │   plan_mode   │  │   critic, reviewer│  │   (subproc, │
        │   review      │  │   code_review,    │  │   own jail) │
        └───────┬───────┘  │   summarizer,     │  └─────────────┘
                │          │   alignment       │
                │          └───────┬───────────┘
                │                  │
        ┌───────▼──────────────────▼────────────┐
        │             tools/dispatch            │
        │  read_file list_dir grep apply_edit   │
        │  run_verify_command [run_command]     │
        └───────────────────┬───────────────────┘
                            │
                  ┌─────────▼─────────┐
                  │  sandbox/jail.py  │
                  └─────────┬─────────┘
                            │ JSON policy
                  ┌─────────▼─────────┐
                  │  agent6-jail      │  (Rust; userns + landlock + seccomp)
                  └───────────────────┘

Dependency direction is enforced by tach: cli → workflows → agents → tools → sandbox. Workflows never import each other; agents never import workflows or the CLI.

Requirements

• Linux. macOS and Windows are not supported and never will be — the sandbox uses Linux-only kernel APIs (Landlock, seccomp-bpf, user/mount namespaces, pivot_root).
• Linux kernel ≥ 6.7 for full Landlock TCP-connect rules. Older kernels fall back to filesystem-only Landlock with a loud warning.
• kernel.unprivileged_userns_clone = 1 (default on Ubuntu, Debian, and most cloud images). Required for the strict sandbox profile; without it the agent falls back to hardened or refuses, per config.
• Python ≥ 3.12.
• Anthropic and/or OpenAI-compatible API key.

If installing from source, you also need:

• A Rust toolchain on PATH (cargo, rustc). The hatch build hook invokes cargo build to compile agent6-jail. It does not install Rust for you — if cargo is not on PATH the hook skips with a message and the resulting install has no jail binary (agent6 check-sandbox will tell you).
• Released PyPI wheels bundle a prebuilt agent6-jail and have no Rust toolchain requirement.

Install

From source (development):

git clone https://github.com/<you>/agent6
cd agent6
uv sync --extra tui
uv run agent6 --help

uv sync runs hatch_build.py, which:

1. invokes cargo build --release --locked --manifest-path jail/Cargo.toml
2. copies the resulting agent6-jail into src/agent6/sandbox/_bin/agent6-jail (gitignored)

The [tui] extra pulls in textual for the live dashboard. Skip it with uv sync if you don't want the TUI.

From PyPI (once released):

uv tool install agent6

PyPI wheels ship with the jail binary inside. To override the bundled binary (custom build, alternate path), set AGENT6_JAIL_BIN=/path/to/agent6-jail.

Shell tab-completion

agent6 supports tab-completion for all subcommands and flags via argcomplete. To enable it for your current shell, source the completion script once:

# Bash (add to ~/.bashrc to persist).
eval "$(register-python-argcomplete agent6)"

# Zsh (add to ~/.zshrc; needs `autoload -U compinit && compinit` first).
eval "$(register-python-argcomplete agent6)"

# Fish (one-time write).
register-python-argcomplete --shell fish agent6 > ~/.config/fish/completions/agent6.fish

Or, for system-wide completion in all shells, run activate-global-python-argcomplete once (see argcomplete docs).

Quick start

export ANTHROPIC_API_KEY=sk-ant-...

# Scaffold agent6.toml + AGENTS.md and add .agent6/ to .gitignore.
agent6 init

# Sanity checks.
agent6 check-config
agent6 check-sandbox

# Plan-only: cheap pre-flight, no code changes.
agent6 plan new "add a --json output mode to the CLI"

# Inspect a previously persisted plan (defaults to most recent).
agent6 plan show

# Apply free-form feedback to the last plan, producing a new run.
agent6 plan revise "split step 2 into smaller commits"

# Hand-edit the plan JSON in $EDITOR, producing a new run.
agent6 plan edit

# Offline Q&A: if the critic raises clarifying questions, write
# them to a file, fill in the 'answer' fields, then re-run.
agent6 plan new --questions-file q.json "add a --json output mode"
$EDITOR q.json
agent6 plan new --run-id <same-id> --answers-file q.json "add a --json output mode"

# Full implement workflow. --yes auto-confirms the plan.
agent6 run --yes "add a --json output mode to the CLI"

# Resume an interrupted run (refuses if the worktree diverged).
agent6 resume <run-id>

# Read-only code review of a diff. Never touches the worktree.
agent6 review --base origin/main --head HEAD

Other commands:

• agent6 watch [<run-id>] — attach the live TUI dashboard to an existing run (defaults to the most recent). Same view that agent6 run auto-launches in a TTY. Attach and detach freely.
• agent6 memory — manage persistent agent memory under .agent6/memory/.
• agent6 history — search transcripts and run data under .agent6/runs/. Subcommands:
  • agent6 history search <query> — ripgrep-backed text search.
  • agent6 history graph [<run-id>] — render the persisted task graph for a run as a DFS-ordered tree (defaults to the most recent run).
• agent6 --help — full subcommand list.

Configuration

Every field in agent6.toml is required. No implicit defaults. Start from agent6.example.toml.

Highlights:

[sandbox]
profile = "auto"             # auto | strict | hardened
network = "provider_only"    # no | provider_only | allow
run_commands = "ask"         # yes | no | ask

[git]
require_clean_worktree = true
auto_stash = false
branch_per_run = true
commit_strategy = "per_step"  # per_step | squash | stage | none
allow_push = false           # cannot be true; ignored if set
allow_force = false
allow_history_rewrite = false

[workflow]
default = "implement"
verify_command = ["uv", "run", "pytest", "-x"]

[budget]
max_input_tokens  = 2000000
max_output_tokens = 200000

Sandbox profiles:

• strict — user/mount/pid/ipc/uts/net namespaces + pivot_root into a minimal rootfs + Landlock + seccomp + capset(0) + rlimits + NO_NEW_PRIVS. Requires unprivileged user namespaces.
• hardened — no namespaces, but still Landlock + seccomp + capset(0)
  • rlimits + NO_NEW_PRIVS. Works inside default-seccomp Docker.
• auto — pick strict if the kernel allows, else hardened. Logs the chosen profile on every run.

Network modes are enforced by the jail's net-namespace setup (in strict) or by Landlock's TCP-connect rules (kernel ≥ 6.7) on the agent process.

Providers and sub-agents

Declare any number of providers as [providers.<name>] blocks. Each block sets kind = "anthropic" or kind = "openai" and has its own base_url and api_key_env. OpenAI, OpenRouter, Ollama, vLLM, llama.cpp, LM Studio etc. coexist under whatever names you pick.

Each sub-agent has a fixed system prompt, a pydantic-typed output schema, and only the tools its workflow gives it. Routing per role:

Sub-agent	Routed by	Purpose
planner	[models.planner]	Decomposes the refined task into ordered steps.
worker	[models.worker]	Executes one plan step using the tool surface.
critic	[models.critic]	Raises open questions; aborts on real ambiguity.
reviewer	[models.reviewer]	Reviews each step's diff; approves or asks for fixes.
code_review	[models.reviewer]	Powers agent6 review: read-only review of an arbitrary diff.
summarizer	[models.summarizer]	Compresses long verify output / file context to fit budgets.
alignment	[models.worker]	Guards agent6 resume: refuses if the worktree diverged.
planner_revise	[models.planner]	Revises a plan in response to a critic or reviewer objection.

Mixing vendors across roles (e.g. Anthropic planner + OpenRouter worker

• Anthropic reviewer) helps catch shared-failure blind spots.

Workflows

• implement — plan → critic → worker (loop) → reviewer per step. Verify runs after every step; failures retry within the step budget. State is persisted to .agent6/runs/<run-id>/.
• plan_mode — produce a frozen plan only. Useful as a cheap "is the plan reasonable?" pre-flight.
• review — drives the code_review sub-agent on a working-tree, branch-vs-base, or <base>..<head> diff. Always read-only.

Tool surface given to the LLM

Fixed and audited in src/agent6/tools/schema.py:

• read_file(path, start_line?, end_line?)
• list_dir(path)
• grep(pattern, path?, glob?)
• apply_edit(path, edits: list[{kind: "replace"|"create", old_string?, new_string}])
• run_verify_command() — runs workflow.verify_command only
• run_command(argv) — only if sandbox.run_commands ∈ {"yes", "ask"}

There is no write_file, no shell, no web_fetch. Adding a tool requires a security review note in the commit message.

Cost accounting

Every run prints a per-model token + cost summary at the end:

Token + cost summary:
  claude-opus-4-5:    in=18054 out=425  cache_r=0 cache_c=0 calls=1 $0.3027
  claude-sonnet-4-5:  in=8884  out=1171 cache_r=0 cache_c=0 calls=4 $0.0442
  TOTAL: in=26938/2000000 out=1596/200000 cost~$0.3469

Pricing lives in src/agent6/budget.py and is updated by hand from the Anthropic and OpenAI public pages. Budgets in agent6.toml hard-stop the run; a stopped run is resumable.

Live event log + TUI

Every run writes a structured JSONL event stream to .agent6/runs/<run-id>/logs.jsonl. The vocabulary is small and stable:

Event	Emitted by	Notable fields
run.start	implement workflow	user_task
plan.ready	implement workflow	summary, steps[]
step.start / step.end	implement workflow	index, title, status, commit_sha
step.diff	implement workflow	index, commit_sha, patch (truncated)
tool.call / .result	tool dispatcher	name, args (preview), ok, summary
verify.start / .end	tool dispatcher	cmd, exit_code, duration_s, *_tail
role.call / .result	provider wrapper	role, model, tokens_in, tokens_out
budget.update	provider wrapper	totals + caps for input/output tokens
approval.prompt/.answer	tool dispatcher	id, prompt, approved, source
run.end	implement workflow	all_passed

The shape is the data contract for any external viewer. The fold from event stream to UI state lives in src/agent6/ui/state.py as a pure function and is intended to be ported 1:1 to TypeScript.

When agent6 is installed with the tui extra and stdout is a TTY, agent6 run spawns a separate process running python -m agent6.ui --watch <run-dir> that tails logs.jsonl and renders a plan tree, budget bar, tool table, log tail, and the latest step diff. The TUI is read-only on the log; the only thing it writes is <run-dir>/approvals/<id>.answer when the user clicks Allow/Deny on a run_command approval modal. Killing the TUI does not affect the workflow — it falls back to a plain stdin prompt. Pass --no-tui to disable, or attach later with agent6 watch.

Persistence

Each run writes to .agent6/runs/<run-id>/:

• graph.jsonl — append-only journal of every mutation to the task graph.
• graph.dot — current task graph (regenerated atomically on topology change).
• nodes/*.md — one markdown file per node; rewritten atomically.
• logs.jsonl — per-event log (planner output, tool calls, costs).
• transcripts/ — full provider request/response pairs for replay.

A separate agent6-curator subprocess owns all writes to this directory and runs under its own jail policy allowing writes only to .agent6/. The main agent process talks to it over a Unix domain socket; no other process has authority to mutate the graph.

Benchmark

See bench/results.md for a 4-task synthetic benchmark (bug fix, add CLI flag, refactor, type annotations). First run completed 0/4 tasks for ~$0.08 of spend and surfaced four reproducible workflow issues with concrete suggested fixes. Re-run with:

bash bench/run_bench.sh
cat /tmp/agent6-bench/*/result.json

A direct head-to-head against claude-code and other coding agents is not in this repo — it would need a shared task set and a neutral runner.

Repository layout

src/agent6/
  cli.py            argparse entry points
  config.py         pydantic-strict config (all fields required)
  budget.py         per-model pricing + per-run accounting
  events.py         structured run-event log
  git_ops.py        pure-function git wrappers; refuses push/force/rewrite
  memory.py         persistent agent memory (read/write/delete)
  detect.py         kernel + container capability detection
  init.py           `agent6 init` scaffolding
  agents/           typed sub-agent prompts and pydantic IO schemas
  workflows/        deterministic Python orchestrators (implement, plan, review)
  tools/            dispatcher + schemas for the fixed LLM tool surface
  providers/        Anthropic + OpenAI HTTP clients (httpx, no SDK)
  sandbox/          jail.py (Python wrapper) + landlock.py (process-side)
  graph/            curator subprocess + UDS IPC + on-disk graph store
  ui/               pure event-fold + stdlib JSONL tailer + optional textual TUI
jail/               Rust crate for the agent6-jail launcher
tests/
  unit/             ~150 unit tests
  integration/      crash-resume, curator IPC, plan-mode, alignment
  sandbox/          live jail smoke tests + landlock probes
  security/         prompt-injection corpus tests
bench/              synthetic benchmark harness + results
.github/workflows/  build, ci, pypi (Trusted Publishing)

Roadmap

Open work, in priority order:

1. Fix the four bench findings (F1–F4 in bench/results.md): per-step verify gating, edit-by-old-string fragility on consecutive steps, critic conservatism, run-log-before-dirty-check race.
2. Network-egress test corpus — adversarial tests that try to exfiltrate via DNS, ICMP, IPv6, and unix sockets and assert they are all blocked under network = "provider_only".
3. agent6 init --template — write a starter AGENTS.md for common stacks (Python lib, Node app, …) instead of just a stub.
4. Headless run mode — non-interactive --no-confirm-anything for CI; today --yes auto-confirms the plan only, not every run_commands prompt.
5. agent6 review against a remote PR — fetch + review without checkout.
6. First PyPI release — wired in .github/workflows/pypi.yml via Trusted Publishing inside a manylinux container so the bundled agent6-jail links against an old enough glibc. Blocked on items 1–2.

Contributing

Read AGENTS.md before sending a PR. The repo's verify_command is the single source of truth for "is this PR landable":

uv run ruff check && uv run ruff format --check && \
  uv run pyright && uv run tach check && uv run pytest

Security-sensitive changes (anything in sandbox/, tools/, git_ops, providers/, graph/curator) must include a security review note in the commit message.

License

Apache License 2.0. See LICENSE for the full text. Every source file carries an SPDX-License-Identifier: Apache-2.0 header and a Copyright 2026 Eric Lesiuta notice.