Cirdan
Cirdan is an on-call software repair agent. A production alert fires — Grafana,
Alertmanager, or Slack. Cirdan resolves the affected service and its repo from the
explicit services: registry in cirdan.yaml, reproduces the failure in an isolated
runner (Docker Compose or Kubernetes), has a coding agent fix the code — your own
logged-in Claude Code / Codex CLI, or an API provider — re-verifies the fix against
the pinned reproduction probe and the repo's test suite, and opens a verified pull
request. When policy allows, it merges, deploys, and verifies production recovery,
stopping at manual_required with full evidence when recovery fails.
alert ─▶ resolve service + repo (the services: registry) ─▶ reproduce in an isolated runner
─▶ coding agent fixes the code ─▶ verify (pinned repro probe + sandboxed test suite)
─▶ verified PR (@cirdan review loop; CI checks watched) ─▶ optional merge + deploy
─▶ verify recovery in productionThe job it does: when an alert fires at 3am for a code-shaped failure, a verified fix PR (or a completed deploy plus recovery confirmation) is waiting instead of a page.
Cirdan is deliberately not an infrastructure mapper, a topology explorer, an observability dashboard, a generic agent launcher, or a ChatOps bot. It repairs the services you register — nothing is discovered, and nothing is repaired implicitly.
Quickstart
pipx install "cirdanops[all]" # or uv / pip / npm / brew / curl / docker — see Install
cirdan setup # opens the local, loopback-only setup UIcirdan setup walks one short path and shows a readiness banner that flips to
"Ready to repair" only when this install can actually fix something:
- Choose a pathway — Use the CLI (the tools already logged in on this machine) or Use the API (managed credentials + a GitHub App). See Two ways to run.
- Connect an alert source — a Grafana webhook (+ HMAC), native Alertmanager intake, or Slack.
- Select repair repositories — in Source Code Connection, Cirdan lists the
repos your
ghlogin can push to; pick which ones it may repair. Only selected repositories are ever repaired. - Prove routing — the Alert routing step synthesizes a sample alert (or takes a real payload you paste) and must show it resolving to a selected repository and routing to a code-repair pipeline.
- Start the daemon and post a demo alert:
cirdand serve --http
curl -X POST localhost:8090/v1/ingest/grafana -d @examples/demo/alert.firing.jsonThe runnable demo in examples/demo/ wires this end to end. The
same checklist is available headlessly — cirdan status --checks prints the identical
table and exits 1 until the install is ready. Useful setup flags:
cirdan setup --terminal— the text step flow instead of the UIcirdan setup --all— run every step without prompting (scripts / CI)cirdan setup --system— machine-level scope in~/.cirdaninstead of a repo
Install
From PyPI (recommended):
uv tool install "cirdanops[all]"
# or
pipx install "cirdanops[all]"
pip install "cirdanops[all]"Without Python — npm / Homebrew / curl:
npx -y @cirdanops/cli serve-mcp # run the MCP server, zero install
npm install -g @cirdanops/cli # or put the `cirdan` command on your PATH
brew install adanb13/tap/cirdan # macOS / Linux (Homebrew)
curl -LsSf https://raw.githubusercontent.com/adanb13/cirdan/main/packaging/install.sh | sh
# Windows: irm https://raw.githubusercontent.com/adanb13/cirdan/main/packaging/install.ps1 | iexThese ship a self-contained binary — no Python 3.11+ required. Supported: macOS (arm64), Linux x64/arm64 (glibc), Windows x64. On Intel Macs, Alpine/musl, or other platforms, use the PyPI install above.
Then set it up in one command (see Quickstart):
cirdan setup # inside a repo
# or, machine-level scope in ~/.cirdan:
cirdan setup --systemBoth open the same guided setup: choose a pathway, connect an alert source + GitHub, select repair repositories, prove routing, and start the always-on daemon.
Targeted installs: cirdanops[mcp], cirdanops[api], cirdanops[slack],
cirdanops[agent], cirdanops[github-app], cirdanops[secrets], or combinations
like cirdanops[api,mcp]. The sandbox runners need no extras — they use the
docker/kubectl CLIs already on your PATH.
Prerequisites by platform (Python 3.11+ and uv or pipx):
# macOS
brew install python@3.12 uv
# Windows
winget install astral-sh.uv
# Ubuntu / Debian
sudo apt install python3.12 python3-pip pipx
# or get uv:
curl -LsSf https://astral.sh/uv/install.sh | shDocker (no Python needed):
# run the always-on repair daemon: alert receiver + isolated repair runner,
# using the host's Docker for sandboxes
docker run -d \
-v "$PWD":/workspace:ro \
-v /var/run/docker.sock:/var/run/docker.sock \
-p 127.0.0.1:8090:8090 \
ghcr.io/adanb13/cirdan(or docker compose up with the provided docker-compose.yml)
From source (latest unreleased):
pip install "cirdanops[all] @ git+https://github.com/adanb13/cirdan.git"Two commands are installed:
| Command | What it is |
|---|---|
cirdan | Human/agent CLI |
cirdand | Long-running Always ON daemon |
Local development (from a clone)
Contributors work from a clone with an editable virtualenv, so changes to the
working tree take effect immediately — no reinstall between edits. make install
creates .venv and installs the package (distribution name cirdanops) editable with
the [all,dev] extras — every runtime feature plus the test toolchain:
git clone https://github.com/adanb13/cirdan.git
cd cirdan
make install # ≈ python3 -m venv .venv && .venv/bin/pip install -e ".[all,dev]"
make test # .venv/bin/python -m pytest tests/ -qRequires Python 3.11+. The manual two-line equivalent works on a standard Python;
make install additionally handles the pip-less-venv case (it falls back to
python3 -m venv --without-pip and bootstraps pip into the venv).
The editable install puts both console scripts in .venv/bin, running working-tree
code with no rebuild:
.venv/bin/cirdan setup # or: .venv/bin/python -m cirdan.cli.main setup
.venv/bin/cirdand serve --http
.venv/bin/python -m pytest tests/test_slack_events.py -q # a single test moduleCommon Make targets (make help lists them all):
| target | what it does |
|---|---|
make install | create .venv + editable install with [all,dev] |
make test | run the full pytest suite |
make build | build the sdist + wheel into dist/ |
make setup-wipe DIR=<dir> [KEY=1] | reset a project's onboarding so cirdan setup restarts from step 0 (KEY=1 also drops the global master key) |
make demo-up … make demo-clean | build and drive the runnable stack in examples/demo/ |
On a headless box with no OS keyring, storing credentials during
cirdan setupneeds a master key in the environment first:export CIRDAN_MASTER_KEY=$(.venv/bin/python -c 'import os,base64;print(base64.b64encode(os.urandom(32)).decode())').
Two ways to run: Use the CLI / Use the API
The first setup screen picks a deployment posture (deployment_mode: in
cirdan.yaml), which gates everything after it:
Use the CLI (cli, the default) — Cirdan runs with the tools already logged in on
this machine. GitHub writes go through your gh auth login; the coding agent is a
detected, logged-in Claude Code or Codex CLI, spawned headless inside the isolated
repair workspace; the sandbox runner is your local Docker (or kubectl). The happy path
needs no stored keys and no GitHub App — an env-var API key and a GitHub App
remain available behind explicitly labeled "Advanced" toggles.
Use the API (api) — headless and managed, for shared/enterprise deployments.
Provider API keys are stored encrypted (cirdan secret; AES-256-GCM), GitHub writes
go through a GitHub App (guided manifest onboarding) with short-lived per-repo
installation tokens, and the enterprise security profile is derived automatically:
inherited gh auth and host-spawned CLI agents are refused at config load.
Both pathways end at the same readiness contract — the setup UI banner and
cirdan status --checks render the same table: repair repositories selected (each with a
resolvable repo) · an alert source connected · a routing proof (a sample or live
alert demonstrably resolved to a selected repository and routed to a code pipeline) ·
remediation.mode ∈ {develop, deliver} · a live-probed coding agent · a verified
GitHub write path including access to each selected repo · git on PATH · a
working sandbox runner · the daemon running. Every red row shows the exact fix
command or the setup step that resolves it.
Legacy configs load forever: deployment_mode: single-user reads as cli,
business as api, and the file text migrates on the next setup save.
Configuration
cirdan setup writes cirdan.yaml for you; everything is also hand-editable — see
cirdan.yaml.example. The heart of the file is the
services: registry: the explicit list of services Cirdan may repair, how alerts
resolve to them, and where their code lives.
services:
- name: checkout-api # canonical id (lowercase, node-id-safe)
repo: acme/checkout # "org/name" — the PR / repair target
aliases: [checkout, checkout-svc] # extra alert-label names for this service
match_labels: {team: payments} # optional exact label matchers (first match wins)
deploy: # how it runs in prod + how the runner rebuilds it
kind: compose # compose | k8s | helm
compose_service: checkout-api # defaults to the entry name
compose_files: [docker-compose.yml]
deploy_workflow: deploy.yml # per-service GitHub Actions deploy (optional)
telemetry_service: checkout # Loki/PromQL service label; defaults to name
- name: payments-api
repo: acme/payments
source_root: ~/src/payments # local checkout (cli pathway only)
deploy:
kind: k8s
namespace: prod
workload: payments-api # kubernetes_kind defaults to DeploymentAlerts resolve to a service by an explicit cirdan_node label, then match_labels,
then a ladder of common labels (service, service_name, app, job,
deployment, statefulset, pod, container, the host of instance,
annotations.service, alertname) matched against names + aliases. There is no
implicit default: an alert that matches nothing opens a triage incident and never
auto-repairs "the only registered repo".
Routing policy. Every alert source
…