Using Gc

Using GC

Use Gas City only when the caller explicitly selects it. Treat it as a replaceable execution adapter, not a correctness or completion boundary.

Choose the factory first

AgentOps supports both Gas City and the Agentic Coding Flywheel as external software-factory runtimes. Use this skill only for Gas City. If the caller selects the Flywheel, use its native workflow instead of wrapping it in Gas City.

AgentOps supplies skills and evidence contracts to either factory. It does not need its own Gas City formula or role pack. Install or link AgentOps skills into the provider runtime before starting workers; the upstream Mayor, coordinator, and workers can then discover and select plan, implement, test, validate, and other AgentOps skills normally.

Gas City 1.4 operating model

Gas City 1.4 is run-centered. The supervisor serves the dashboard and typed, paginated session/run APIs. Every graph-owning city or rig scope needs its own core.control-dispatcher; that deterministic worker advances formula control beads. Agent workers claim routed work. The upstream gc.mayor skill is the guided coordinator; gc.run-operator launches and supervises formulas.

The normal AgentOps path is:

1. Install and pin the upstream gascity workflow and rig-role imports.
2. Add the project as a rig, prepare its stock maintainer runtime, and make AgentOps skills visible to its provider sessions.
3. Create a caller-owned bead and launch the upstream build-basic, continuation, review, or implementation formula that matches the available artifacts.
4. Read run, session, bead, artifact, and verdict state. Completion is never inferred from chat or pane prose.

Prepare and qualify a rig before its first build with the shipped AgentOps CLI (no repo checkout required):

ao gc prepare --city /path/to/city --rig /path/to/rig
ao gc check --city /path/to/city --rig /path/to/rig

The command verifies the exact official workflow and role pins, snapshots the upstream validation scripts and schemas unchanged inside the rig's .gc runtime, installs only small AgentOps-owned wrappers at the formula check paths, selects an existing Python that can import PyYAML, and links the AgentOps skills into the city and rig Codex sinks. Skills come from the enclosing AgentOps checkout when one is present, otherwise from the installed skills root; pass --skills-source to pin a different directory. It never modifies the GC binary, cache, formulas, roles, or upstream pack. check issues only native inspection commands, writes no adapter files, and fails before model spend when that runtime contract is missing or drifted.

Preferred pack and registries

The built-in main registry catalogs official packs. The community registry is optional configuration:

gc pack registry list
gc pack registry refresh
gc pack registry search --all
gc pack registry show main:gascity
gc pack registry add community https://registry.gascity.com/registry.toml
gc pack registry search --registry community --all

search reads the local registry cache; show reports release provenance and exact import commands. gc import add declares a source/version, and gc import install resolves it into packs.lock. Prefer an exact accepted release for reproducible cities.

AgentOps prefers the official gascity build pack, the workflow family visible in the public Maintainer City factory. The current accepted reference is gascity 0.1.6 at commit 3b3b89f2011e06d84459aa7bea1552382f13930a:

• dashboard: https://factory.gascity.com;
• workflows: build-basic, build-from-*, implement, review, issue, and PR flows;
• stock rig roles: gc.run-operator, gc.implementation-worker, planners, reviewers, and publisher;
• scope-local formula control: core.control-dispatcher;
• guided coordination: the upstream gc.mayor skill.

Install the workflow pack at city scope and its sibling roles pack on every rig that runs work, following the exact commands returned by gc pack registry show main:gascity. Keep the stock gc.* namespace; do not nest or rename the roles behind an AgentOps pack.

For a starter build:

gc bd create "Add a --json flag to the export command"
gc sling gc.run-operator <bead-id> --on build-basic \
  --var artifact_root=plans/json-flag/build

For guided requirements, planning, and launch, tell the active agent:

Use skill gc.mayor

AgentOps skills are tools available to those factory agents, not a replacement workflow. Explicitly name a skill in the bead or prompt when its behavior is required. The current upstream decomposition does not automatically propagate a free-form Required Skills section from the caller-owned source bead into every generated work item. Inspect the decomposition before implementation; put a required skill name on the actual work item or worker prompt when its use is an acceptance condition. Skill presence and skill invocation are different facts.

Upgrade an existing city to 1.4

Before starting its orchestrator, run once per city:

gc doctor --fix
gc import install
gc supervisor stop --wait   # macOS when an older direct supervisor remains
gc start

Then confirm:

• gc version reports 1.4.0 from the intended path;
• gc doctor has no blocking failures;
• each graph-owning rig has an unsuspended core.control-dispatcher;
• imports and packs.lock resolve;
• ao gc check accepts the contained maintainer runtime and AgentOps skill links;
• on macOS, the supervisor LaunchAgent resolves to the same executable as the selected gc binary;
• old standalone-dashboard bookmarks or reverse proxies are removed.

A stale registered city may block every start. Repair that city with gc doctor --fix, or explicitly unregister it if it is intentionally retired.

Retire an old HQ/canary by exact registered name or path, without stopping the machine-wide supervisor needed by its replacement:

gc cities --json
gc stop /path/to/old-city --timeout 45s
gc unregister /path/to/old-city
gc cities --json

unregister fails rather than silently accepting an unknown target. Preserve the city directory until its Beads state is backed up or confirmed disposable. Create the replacement from the upstream Gas City template, install its pinned imports, and verify it with gc cities --json, gc --city <new-city> status, and gc --city <new-city> doctor --json.

Stall protocol

First classify the bead.

• Still ready: dispatch it once to its gc.run_target, then stop and inspect.

• Already routed/in progress: re-slinging is a NO-OP. Wake its owning worker once:

  gc session wake <run_target>
  

Then capture the exact tmux pane named by session state and run gc doctor. Never repair a city from inside that city.

The upstream pack may leave a future affinity-bound step assigned to a session that has already drain-acked. Diagnose this only from outside the city:

ao gc recover-affinity --city /path/to/city --rig /path/to/rig

The default is a dry run. If every listed assignment is correct, repeat with --apply. The bounded repair only clears the assignee on a currently ready formula bead whose gc.session_affinity=require session is no longer live. It does not sling, retry, close, restart, or select work.

Visibility: four layers

1. Supervisor/run state — gc dashboard, run detail, gc status, and gc session list --json. Run detail unifies the stage ladder, structured transcripts, token rate, and estimated burn rate. A roster may still report active while a provider is wedged.
2. Bead graph — gc bd --rig <rig> ready --json and show <id> --json. This is workflow-state truth, but a claimed bead cannot reveal a wedged pane.
3. Pane truth — tmux -L <socket> capture-pane -pt <session>. This exposes trust prompts, update nags, API/DNS failures, and interactive wedges.
4. Health machinery — gc doctor, gc order history, storage health, and events. This proves metabolism, not semantic acceptance.

When layers disagree, trust the more direct observation: pane over roster for a session wedge, bead/run state over prose for workflow completion.

gc status may return a partial no_agents_running snapshot while gc session list --json shows a live Mayor or worker. Treat that as an observability disagreement, not permission to restart. Use session and pane truth for liveness, bead/run state for workflow progress, and Doctor for metabolism. A supervisor with abnormal CPU, a timed-out native stop, or a recurring hook rewrite remains an upstream operational defect; this helper reports it but never kills or patches GC processes.

The caller-owned input bead and the generated workflow root have separate lifecycles. A successful build-basic run may close its workflow root while leaving the input bead open. Likewise, push=false and open_pr=false produce a successful no-op publish while the approved commit remains in its source anchor worktree. Neither state is semantic completion by itself.

Boundaries

• GC quests, runs, attempts, stalls, cancellations, and internal close state stay in GC. They never become AgentOps Plan, Candidate, RPI, or verdict state.
• A GC close or completed run is not AgentOps completion. Only a fresh Validate context issues the semantic result or, when requested, persists verdict.v2.
• This skill performs no automatic selection, retry, semantic validation, Git, integration, closure, release, or delivery.