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The Gas Town Universal Propulsion Principle: If there is work on your hook, YOU MUST RUN IT.
GUPP is the interrupt controller of the Gastown chipset. In a real processor, the interrupt controller converts external events (keyboard press, network packet, timer tick) into CPU interrupts that force immediate handling. Without it, the CPU would have to poll every device continuously, wasting cycles on checks that almost always find nothing. GUPP does the same for AI coding agents: it converts the polled model (agent checks periodically, waits for user input) into an interrupt-driven model (work appears on hook, agent executes immediately).
Why GUPP Exists
LLM coding assistants are trained through RLHF to be helpful, harmless, and honest. A side effect of this training is a strong bias toward waiting for the user -- asking clarifying questions, seeking confirmation before acting, pausing between steps for feedback. This is appropriate in interactive chat but catastrophic for autonomous multi-agent orchestration, where every moment of idle waiting is a moment the pipeline stalls.
Gastown discovered this empirically. Agents spawned with a work item would introduce themselves, summarize their understanding of the task, and then wait. They would ask "Shall I proceed?" when the answer was already on their hook. GUPP was created to override this trained passivity with an explicit, non-negotiable execution mandate.
The principle is simple: if you have hooked work, you do not wait. You do not ask for confirmation. You do not summarize your plan and pause for feedback. You begin execution immediately. This is physics, not politeness. Gastown is a steam engine and you are a piston.
Activation Triggers
This skill activates when:
An agent has work assigned to its hook and is not yet executing
Stall detection identifies an agent with hooked work that has gone idle
A new agent is spawned and needs GUPP enforcement injected into its context
Runtime-specific GUPP strategy selection is needed
Heartbeat supervision needs to be configured for active agents
An agent has been nudged but remains stalled
Per-Runtime Enforcement Strategies
GUPP enforcement adapts to each runtime's capabilities through the Runtime HAL. The HAL detects the active runtime and GUPP selects the highest-fidelity enforcement mechanism available.
Claude Code
Claude Code provides the richest enforcement surface through its session hooks system.
Layer
Mechanism
Details
Primary
hook_injection
SessionStart hook in .claude/settings.json injects GUPP rules and work context before the agent's first prompt. The agent starts in autonomous mode with zero setup latency.
Secondary
prompt_preamble
AUTONOMOUS WORK MODE template prepended to agent context. Reinforces GUPP when hooks fire inconsistently.
Enforcement
deacon_heartbeat
Witness runs the Deacon heartbeat patrol at 2-minute intervals. Detects agents that received hooks but stalled before beginning work.
Watchdog
boot_restart
If an agent remains stalled for 5+ minutes after hook injection, the watchdog requests a session restart. The restarted session re-fires the SessionStart hook, giving GUPP another chance.
Codex
Codex lacks session hooks. GUPP uses startup command injection as the primary strategy.
Layer
Mechanism
Details
Primary
startup_fallback
gt prime command injected via tmux sends the agent's role, bead assignment, and GUPP rules through the startup context.
Secondary
prompt_preamble
AUTONOMOUS WORK MODE template in agent context.
Enforcement
nudge_loop
Witness sends nudges at 1-minute intervals for stall detection. Shorter interval compensates for lower hook fidelity.
Watchdog
boot_restart
Session restart after sustained stall.
Gemini
Gemini has no hook support and limited startup injection. GUPP relies on polling.
Layer
Mechanism
Details
Primary
prompt_preamble
GUPP rules prepended to the agent's prompt context. This is the only reliable injection point.
Secondary
polling
Agent polls state/hooks/{agentId}.json on a timer to detect new work assignments.
Enforcement
nudge_loop
Witness sends nudges at the configured interval.
Watchdog
boot_restart
Session restart after sustained stall.
Strategy Selection
The Runtime HAL exposes getGUPPStrategy() which returns the primary strategy for the detected runtime. Other chipset skills call this method without knowing which runtime is active:
const hal = detectRuntime();
const strategy = hal.getGUPPStrategy();
switch (strategy) {
case'hook_injection':
// Claude Code path: inject via SessionStart hookbreak;
case'startup_fallback':
// Codex path: inject via gt prime commandbreak;
case'polling':
// Gemini/unknown path: agent polls for assignmentsbreak;
}
Configurable Thresholds
All GUPP timing parameters are configurable through the chipset YAML. Defaults are tuned for typical LLM agent behavior but can be adjusted per-project or per-runtime based on observed performance.
gupp:thresholds:stall_detection:300# seconds (5 min) -- time before declaring an agent stallednudge_interval:120# seconds (2 min) -- time between heartbeat checksrestart_threshold:600# seconds (10 min) -- time before requesting session restart
Threshold Reference
Parameter
Default
Range
Purpose
stall_detection
300s (5 min)
60s - 1800s
How long an agent can be idle with hooked work before it is considered stalled
nudge_interval
120s (2 min)
30s - 600s
How often the Deacon heartbeat checks each active agent
restart_threshold
600s (10 min)
120s - 1800s
How long a stalled agent can remain unresponsive before a restart is requested
The Runtime HAL provides per-runtime defaults that override the chipset YAML defaults when a specific runtime is detected. For example, Claude Code uses a 120s stall threshold (the hook system makes stalls more detectable) while Gemini uses 300s (polling introduces latency).
Deacon Heartbeat Pattern
The Deacon heartbeat is the supervision loop that enforces GUPP across all active agents. It runs independently of any individual agent session -- typically inside the witness-observer or as a standalone patrol process.
1. Timer fires (every nudge_interval seconds)
2. For each agent with an active hook:
a. Read last_activity timestamp from state file
b. If now - last_activity > stall_detection:
i. Send nudge via nudge-sync
ii. Record nudge timestamp and count
3. For each previously nudged agent:
a. If still stalled after nudge_interval:
i. Escalate to witness-observer
ii. Witness sends health_escalation mail to mayor
4. For each agent past restart_threshold:
a. Request boot restart via Runtime HAL
b. Increment restart counter for this bead
c. If restart_count >= 3: escalate to human
The full heartbeat protocol is documented in heartbeat.md.
Observable Metrics
GUPP exposes these metrics for skill-creator's pattern detection and adaptive learning. Over time, skill-creator proposes refinements to thresholds and strategy selections based on observed effectiveness.
GUPP Response Time
Time elapsed from hook assignment to first work activity (first commit, first file edit, or first status update). Measured per-agent, per-session.
Ideal: under 30 seconds for Claude Code (hook injection), under 60 seconds for Codex (startup fallback), under 120 seconds for Gemini (polling).
Nudge Effectiveness
Boolean per-nudge: did the agent resume work within nudge_interval seconds after receiving the nudge? Tracks whether nudges are actually fixing stalls or just adding noise.
A nudge effectiveness rate below 50% suggests the stall detection threshold is too aggressive (false positives) or the agent is genuinely stuck and needs restart rather than nudging.
Strategy Success Rate
Per-runtime success rate: what percentage of GUPP activations result in the agent beginning work within the expected response window? Tracks which primary strategy produces the fastest, most reliable GUPP response.
How often agents stall per session. A session with zero stalls is ideal. High stall frequency may indicate a systemic issue (context window exhaustion, ambiguous work items, missing dependencies).
Skill-creator observes these metrics across sessions and proposes adjustments:
Threshold tuning: If stall detection fires frequently but nudge effectiveness is low, increase stall_detection to reduce false positives
Strategy switching: If a runtime's primary strategy has low success rate, recommend switching to the secondary
Interval optimization: If nudge effectiveness is high but response time is long, decrease nudge_interval for faster recovery
Restart policy: If restarts consistently fix stalls, the agent may need better initial context (improve hook injection quality)
Safety Boundaries
GUPP Is Advisory in GSD
GUPP enforcement is ADVISORY within GSD's structured workflow. The GSD orchestrator's phase gates, verification steps, and checkpoint protocols take precedence over GUPP urgency. If a GSD checkpoint requires human verification, GUPP does not override it. If a phase gate blocks progress pending approval, GUPP does not force execution past the gate.
The hierarchy is:
GSD orchestrator (highest authority)
|
v
Phase gates and checkpoints
|
v
GUPP propulsion (execution enforcement)
|
v
Agent autonomy (lowest -- must obey all above)
GUPP operates between the orchestrator's structural gates. Within a phase, within an approved plan, within a committed task -- GUPP demands immediate execution. But it never overrides the orchestrator's decision about what to execute or when a phase is complete.
Restart Limits
The watchdog restart mechanism has strict limits to prevent infinite restart loops:
Parameter
Value
Purpose
Max restart threshold
1800s (30 min)
Hard cap on how long before restart. Cannot be configured higher.
Max restarts per bead
3
After 3 restarts for the same work item, escalation to human is mandatory.
Restart cooldown
60s
Minimum time between consecutive restarts for the same agent.
Human Escalation
After 3 restarts for the same bead without resolution, GUPP stops attempting automated recovery and escalates to a human operator:
if (restartCount >= 3) {
constescalation: AgentMessage = {
from: witnessId,
to: 'mayor',
channel: 'mail',
payload: `HUMAN_ESCALATION: ${beadId} has stalled ${restartCount} times. ` +
`Automated recovery exhausted. Requires human intervention.`,
timestamp: newDate().toISOString(),
durable: true,
};
// Mayor surfaces this to the human operator
}
The mayor receives the escalation and surfaces it through whatever channel the human is monitoring (terminal output, notification file, log). GUPP does not attempt a fourth restart.
No Data Destruction
GUPP enforcement never destroys work in progress. Restarts preserve the agent's branch and commits. Nudges are non-destructive signals. Escalations are informational. At no point does GUPP delete files, reset branches, or discard uncommitted changes.
Integration with Other Gastown Skills
Skill
How GUPP Integrates
runtime-hal
HAL provides getGUPPStrategy(), stall thresholds, and restart capability detection
polecat-worker
Polecats are the primary GUPP enforcement target -- they must act on hooked work
witness-observer
Witness runs the Deacon heartbeat loop that enforces GUPP timing
nudge-sync
GUPP sends nudges through the nudge channel for stall recovery
mail-async
GUPP escalations use durable mail for mayor notifications
beads-state
GUPP reads agent activity timestamps and hook status from state files
hook-persistence
GUPP monitors hook assignments to detect when agents have pending work
mayor-coordinator
Mayor receives escalations and decides on restarts or reassignment
sling-dispatch
Sling sets hooks that activate GUPP enforcement for the assigned agent
References
references/gastown-origin.md -- The GUPP principle from Gastown, how it fights model training bias
references/boundaries.md -- Advisory nature, restart limits, human escalation rules
heartbeat.md -- Deacon heartbeat supervision pattern and integration points
