Auto Mode

Auto mode is GSD’s autonomous execution engine. Run /gsd auto, walk away, come back to built software with clean git history.

How It Works

Auto mode is a state machine driven by files on disk. It reads .gsd/STATE.md, determines the next unit of work, creates a fresh agent session, injects a focused prompt with all relevant context pre-inlined, and lets the LLM execute. When the LLM finishes, auto mode reads disk state again and dispatches the next unit.

The Loop

Each slice flows through phases automatically:

Plan (with integrated research) → Execute (per task) → Complete → Reassess Roadmap → Next Slice
                                                                                      ↓ (all slices done)
                                                                              Validate Milestone → Complete Milestone

• Plan — scouts the codebase, researches relevant docs, and decomposes the slice into tasks with must-haves
• Execute — runs each task in a fresh context window
• Complete — writes summary, UAT script, marks roadmap, commits
• Reassess — checks if the roadmap still makes sense
• Validate Milestone — reconciliation gate after all slices complete; compares roadmap success criteria against actual results, catches gaps before sealing the milestone

Deep Planning Mode

For projects that need more up-front discovery, enable deep planning mode in project preferences:

planning_depth: deep

You can also opt in when starting project setup with /gsd new-project --deep or /gsd new-milestone --deep; GSD writes the project .gsd/PREFERENCES.md setting for you.

Deep mode keeps the normal slice execution loop, but first runs a one-time staged discovery flow before milestone-level planning:

Workflow Preferences -> Project Context -> Requirements -> Research Decision -> Optional Project Research -> Milestone Context/Roadmap

Artifact	When it appears	Purpose
.gsd/PREFERENCES.md	--deep / workflow-preferences	Holds planning_depth: deep and captured workflow settings
.gsd/PROJECT.md	discuss-project	Project vision, users, anti-goals, constraints, and rough milestone sequence
.gsd/REQUIREMENTS.md	discuss-requirements	Capability contract using R### requirements grouped by Active, Validated, Deferred, and Out of Scope
.gsd/runtime/research-decision.json	research-decision	Records research or skip; this unit only asks the question and writes the marker
.gsd/research/STACK.md, FEATURES.md, ARCHITECTURE.md, PITFALLS.md	research-project, only when the decision is research	Four parallel project-level research outputs for stack, feature norms, architecture, and pitfalls
.gsd/milestones/<MID>/M###-CONTEXT.md and M###-ROADMAP.md	Normal milestone discussion/planning	Milestone-specific context and executable roadmap

REQUIREMENTS.md is rendered from the requirements stored in the GSD database. Agents should save individual requirements with gsd_requirement_save; a final gsd_summary_save for REQUIREMENTS will fail if no active requirement rows exist instead of treating caller-supplied markdown as canonical.

Project research is informational, not binding. It cross-checks the requirements and surfaces table stakes, risks, and omissions; any new commitment should be added to .gsd/REQUIREMENTS.md before planning depends on it.

Key Properties

Fresh Session Per Unit

Every task, research phase, and planning step gets a clean context window. No accumulated garbage. No degraded quality from context bloat. The dispatch prompt includes everything needed — task plans, prior summaries, dependency context, decisions register — so the LLM starts oriented instead of spending tool calls reading files.

Runtime Tool Policy

Each auto-mode unit has a UnitContextManifest with a ToolsPolicy, and GSD enforces that policy before tool calls execute. Execution units use all mode and may edit project files, run shell commands, and dispatch subagents. Most planning and discussion units use planning mode: they can read broadly, write planning artifacts under .gsd/, run only read-only shell commands, and cannot dispatch subagents. Selected planning and closeout units use planning-dispatch mode, which keeps the same source-write and bash restrictions but allows subagent dispatch for isolated recon, planning, or review work. Documentation units use docs mode, which keeps the same restrictions but also allows writes to the manifest’s explicit documentation globs such as docs/**, top-level README*.md, CHANGELOG.md, and top-level *.md.

Writes outside those allowed paths, unsafe bash commands, and subagent dispatch from non-dispatch planning units are blocked with a hard policy error instead of relying on prompt compliance. In planning-dispatch units, prompts steer the parent agent toward read-only specialists such as scout, planner, researcher, reviewer, security, or tester; implementation-tier agents still belong in execute-task.

Context Pre-Loading

The dispatch prompt is carefully constructed with:

Inlined Artifact	Purpose
Task plan	What to build
Slice plan	Where this task fits
Prior task summaries	What’s already done
Dependency summaries	Cross-slice context
Roadmap excerpt	Overall direction
Decisions register	Architectural context

The amount of context inlined is controlled by your token profile. Budget mode inlines minimal context; quality mode inlines everything.

Git Isolation

GSD isolates milestone work using one of three modes (configured via git.isolation in preferences):

• none (default): Work happens directly on your current branch. No worktree, no milestone branch. Ideal for hot-reload workflows where file isolation breaks dev tooling.
• worktree: Each milestone runs in its own git worktree at .gsd/worktrees/<MID>/ on a milestone/<MID> branch. Worktree mode requires at least one commit; in a zero-commit repo with no committed HEAD, GSD temporarily runs as none until the first commit exists. All slice work commits sequentially, and the milestone is squash-merged to main as one clean commit.
• branch: Work happens in the project root on a milestone/<MID> branch. Useful for submodule-heavy repos where worktrees don’t work well.

See Git Strategy for details.

Parallel Execution

When your project has independent milestones, you can run them simultaneously. Each milestone gets its own worker process and worktree. See Parallel Orchestration for setup and usage.

Crash Recovery

A lock file tracks the current unit. If the session dies, the next /gsd auto reads the surviving session file, synthesizes a recovery briefing from every tool call that made it to disk, and resumes with full context.

Headless auto-restart (v2.26): When running gsd headless auto, crashes trigger automatic restart with exponential backoff (5s → 10s → 30s cap, default 3 attempts). Configure with --max-restarts N. SIGINT/SIGTERM bypasses restart. Combined with crash recovery, this enables true overnight “run until done” execution.

Provider Error Recovery

GSD classifies provider errors and auto-resumes when safe:

Error type	Examples	Action
Rate limit	429, “too many requests”	Auto-resume after retry-after header or 60s
Server error	500, 502, 503, “overloaded”, “api_error”	Auto-resume after 30s
Permanent	”unauthorized”, “invalid key”, “billing”	Pause indefinitely (requires manual resume)

No manual intervention needed for transient errors — the session pauses briefly and continues automatically.

Incremental Memory (v2.26)

GSD maintains a KNOWLEDGE.md file — an append-only register of project-specific rules, patterns, and lessons learned. The agent reads it at the start of every unit and appends to it when discovering recurring issues, non-obvious patterns, or rules that future sessions should follow. This gives auto-mode cross-session memory that survives context window boundaries.

Context Pressure Monitor (v2.26)

When context usage reaches 70%, GSD sends a wrap-up signal to the agent, nudging it to finish durable output (commit, write summaries) before the context window fills. This prevents sessions from hitting the hard context limit mid-task with no artifacts written.

Meaningful Commit Messages (v2.26)

Commits are generated from task summaries — not generic “complete task” messages. Each commit message reflects what was actually built, giving clean git log output that reads like a changelog.

Stuck Detection (v2.39)

GSD uses a sliding-window analysis to detect stuck loops. Instead of a simple “same unit dispatched twice” counter, the detector examines recent dispatch history for repeated patterns — catching cycles like A→B→A→B as well as single-unit repeats. On detection, GSD retries once with a deep diagnostic prompt. If it fails again, auto mode stops so you can intervene.

The sliding-window approach reduces false positives on legitimate retries (e.g., verification failures that self-correct) while catching genuine stuck loops faster.

Artifact Verification Retries

After each unit, GSD verifies that the expected artifact exists on disk. If the artifact is missing, auto mode re-dispatches the unit with explicit failure context and records an artifact-verification-retry journal event.

Artifact verification retries are capped at 3 attempts. If the expected artifact is still missing after those retries, GSD pauses auto mode with an “Artifact still missing…” error instead of relying on loop detection or an unbounded dispatch counter.

Post-Mortem Investigation (v2.40)

/gsd forensics is a full-access GSD debugger for post-mortem analysis of auto-mode failures. It provides:

• Anomaly detection — structured identification of stuck loops, cost spikes, timeouts, missing artifacts, and crashes with severity levels
• Unit traces — last 10 unit executions with error details and execution times
• Metrics analysis — cost, token counts, and execution time breakdowns
• Doctor integration — includes structural health issues from /gsd doctor
• LLM-guided investigation — an agent session with full tool access to investigate root causes

/gsd forensics [optional problem description]

See Troubleshooting for more on diagnosing issues.

Timeout Supervision

Three timeout tiers prevent runaway sessions:

Timeout	Default	Behavior
Soft	20 min	Warns the LLM to wrap up
Idle	10 min	Detects stalls, intervenes
Hard	30 min	Pauses auto mode

Recovery steering nudges the LLM to finish durable output before timing out. Configure in preferences:

auto_supervisor:
  soft_timeout_minutes: 20
  idle_timeout_minutes: 10
  hard_timeout_minutes: 30

Cost Tracking

Every unit’s token usage and cost is captured, broken down by phase, slice, and model. The dashboard shows running totals and projections. Budget ceilings can pause auto mode before overspending.

See Cost Management.

Adaptive Replanning

After each slice completes, the roadmap is reassessed. If the work revealed new information that changes the plan, slices are reordered, added, or removed before continuing. This can be skipped with the balanced or budget token profiles.

Verification Enforcement (v2.26)

Configure shell commands that run automatically after every task execution:

verification_commands:
  - npm run lint
  - npm run test
verification_auto_fix: true    # auto-retry on failure (default)
verification_max_retries: 2    # max retry attempts (default: 2)

Failures trigger auto-fix retries — the agent sees the verification output and attempts to fix the issues before advancing. This ensures code quality gates are enforced mechanically, not by LLM compliance.

Slice Discussion Gate (v2.26)

For projects where you want human review before each slice begins:

require_slice_discussion: true

Auto-mode pauses before each slice, presenting the slice context for discussion. After you confirm, execution continues. Useful for high-stakes projects where you want to review the plan before the agent builds.

HTML Reports (v2.26)

After a milestone completes, GSD auto-generates a self-contained HTML report in .gsd/reports/. Reports include project summary, progress tree, slice dependency graph (SVG DAG), cost/token metrics with bar charts, execution timeline, changelog, and knowledge base. No external dependencies — all CSS and JS are inlined.

auto_report: true    # enabled by default

Generate manually anytime with /gsd export --html, or generate reports for all milestones at once with /gsd export --html --all (v2.28).

Failure Recovery (v2.28)

v2.28 hardens auto-mode reliability with multiple safeguards: atomic file writes prevent corruption on crash, OAuth fetch timeouts (30s) prevent indefinite hangs, RPC subprocess exit is detected and reported, and blob garbage collection prevents unbounded disk growth. Combined with the existing crash recovery and headless auto-restart, auto-mode is designed for true “fire and forget” overnight execution.

Pipeline Architecture (v2.40)

The auto-loop is structured as a linear phase pipeline rather than recursive dispatch. Each iteration flows through explicit stages:

1. Pre-Dispatch — validate state, check guards, resolve model preferences
2. Dispatch — execute the unit with a focused prompt
3. Post-Unit — close out the unit, update caches, run cleanup
4. Verification — optional validation gate (lint, test, etc.)
5. Stuck Detection — sliding-window pattern analysis

This linear flow is easier to debug, uses less memory (no recursive call stack), and provides cleaner error recovery since each phase has well-defined entry and exit conditions.

Real-Time Health Visibility (v2.40)

Doctor issues (from /gsd doctor) now surface in real time across three places:

• Dashboard widget — health indicator with issue count and severity
• Workflow visualizer — issues shown in the status panel
• HTML reports — health section with all issues at report generation time

Issues are classified by severity: error (blocks auto-mode), warning (non-blocking), and info (advisory). Auto-mode checks health at dispatch time and can pause on critical issues.

Skill Activation in Prompts (v2.39)

Configured skills are automatically resolved and injected into dispatch prompts. The agent receives an “Available Skills” block listing skills that match the current context, based on:

• always_use_skills — always included
• prefer_skills — included with preference indicator
• skill_rules — conditional activation based on when clauses

See Configuration for skill routing preferences.

Controlling Auto Mode

Start

/gsd auto

Pause

Press Escape. The conversation is preserved. You can interact with the agent, inspect state, or resume.

Resume

/gsd auto

Auto mode reads disk state and picks up where it left off.

Stop

/gsd stop

Stops auto mode gracefully. Can be run from a different terminal.

Steer

/gsd steer

Hard-steer plan documents during execution without stopping the pipeline. Changes are picked up at the next phase boundary.

Capture

/gsd capture "add rate limiting to API endpoints"

Fire-and-forget thought capture. Captures are triaged automatically between tasks. See Captures & Triage.

Visualize

/gsd visualize

Open the workflow visualizer — interactive tabs for progress, dependencies, metrics, and timeline. See Workflow Visualizer.

Remote Control via Telegram

When Telegram is configured as your remote channel, you can control auto-mode and query project status directly from the Telegram chat — without touching the terminal.

Command	What it does
/pause	Pause auto-mode after the current unit finishes
/resume	Clear a pause directive and continue auto-mode
/status	Show current milestone, active unit, and session cost
/progress	Roadmap overview (done / open milestones)
/budget	Token usage and cost for the current session
/log [n]	Last n activity log entries (default: 5)

GSD polls for incoming Telegram commands every ~5 seconds while auto-mode is active. Commands are only available during active auto-mode sessions.

See Remote Questions — Telegram Commands for the full command reference and setup instructions.

Dashboard

Ctrl+Alt+G or /gsd status shows real-time progress:

• Current milestone, slice, and task
• Auto mode elapsed time and phase
• Per-unit cost and token breakdown
• Cost projections
• Completed and in-progress units
• Pending capture count (when captures are awaiting triage)
• Parallel worker status (when running parallel milestones — includes 80% budget alert)

Phase Skipping

Token profiles can skip certain phases to reduce cost:

Phase	budget	balanced	quality
Milestone Research	Skipped	Runs	Runs
Slice Research	Skipped	Skipped	Runs
Reassess Roadmap	Skipped	Runs	Runs

See Token Optimization for details.

Dynamic Model Routing

When enabled, auto-mode automatically selects cheaper models for simple units (slice completion, UAT) and reserves expensive models for complex work (replanning, architectural tasks). See Dynamic Model Routing.

Reactive Task Execution

Reactive task execution is enabled by default. During task execution, GSD derives a dependency graph from the IO annotations in task plans. When at least three ready tasks can be considered safely, tasks that do not conflict (no shared file reads/writes) are dispatched in parallel via subagents, while dependent tasks wait for their predecessors to complete.

reactive_execution:
  enabled: false    # opt out; omit this block to keep the default-on behavior

The graph derivation is pure and deterministic: it resolves a ready-set of tasks, detects conflicts, and guards against deadlocks. If the graph is ambiguous or fewer than the threshold number of ready tasks are available, auto-mode falls back to the normal sequential executor. Setting reactive_execution.enabled: true explicitly keeps the earlier opt-in threshold of two ready tasks; omitting the setting uses the safer default-on threshold of three. Verification results carry forward across parallel batches, so tasks that pass verification don’t need to be re-verified when subsequent tasks in the same slice complete.

Optional tuning:

reactive_execution:
  enabled: true              # explicit opt-in threshold: 2 ready tasks
  max_parallel: 4            # default: 2, allowed range: 1-8
  isolation_mode: same-tree  # currently the only supported isolation mode
  subagent_model: claude-sonnet-4-6

The implementation lives in reactive-graph.ts (graph derivation, ready-set resolution, conflict/deadlock detection) with integration into auto-dispatch.ts and auto-prompts.ts.