Aod Run

Full Lifecycle Orchestrator Skill

Purpose

Single-command lifecycle orchestrator that chains all 5 AOD stages autonomously, pausing at governance gates for Triad sign-offs and persisting state to disk for session resilience. After Deliver completes, the user runs /aod.document separately for human-driven quality review (Stage 6).

Entry Points:

• Raw idea: "description" → start at Discover
• Issue number: #NNN or NNN → resume from issue's current stage
• Resume: --resume → continue from last state checkpoint
• Status: --status / --status #NNN → read-only display

State File: .aod/run-state.json (atomic write-then-rename via run-state.sh)

Navigation

Execution

When this skill is invoked, the command file passes a parsed mode and arguments:

Mode: {idea | issue | resume | status}
Issue: {number or "none"}
Idea: {text or "none"}
DryRun: {true or false}

Step 1: Route by Mode

Read the mode and DryRun flag from the invocation context. Route to the appropriate handler:

DryRun + Status check (first): If DryRun == true AND Mode == status, display "Note: --status is already read-only. --dry-run flag ignored." and route to Status Entry as normal.

DryRun check (second): If DryRun == true (and Mode is NOT status):

MANDATORY: You MUST use the Read tool to load references/dry-run.md before proceeding with dry-run handling. Do NOT rely on memory of prior dry-run content. If the file cannot be read, display an error and STOP.

Follow the Dry-Run Entry instructions from that file. The Dry-Run Entry handler will perform read-only detection and display a preview, then exit without entering the Core Loop.

Mode routing (if DryRun is false):

MANDATORY: You MUST use the Read tool to load references/entry-modes.md before proceeding with any entry mode handler. Do NOT rely on memory of prior entry mode content. If the file cannot be read, display an error and STOP.

After the entry handler sets up state, all modes (except status) converge to the Consent Prompt, then the Core Loop.

Step 1b: Autonomous Mode Consent

Before entering the Core Loop, display the autonomous mode consent prompt and capture the user's choice. This is the only human interaction point in the entire autonomous run.

Display:

AOD ORCHESTRATOR — Autonomous Mode
====================================
This will run the full lifecycle autonomously:

  Discover → Define → Plan → Build → Deliver

Autonomous mode will:
  - Auto-select defaults for all interactive prompts
  - Auto-retry governance rejections (up to 3 attempts)
  - Halt on circuit breaker or BLOCKED (requires manual fix + resume)
  - Split across sessions if the feature is too large

All decisions are logged to run-state.json for post-run review.

After delivery, run /aod.document for human quality review
(code simplification, docstrings, CHANGELOG, API docs).

Proceed? (Y/n)

Handle response:

• Yes (or empty/default): Set autonomous_mode = true. All stage skill invocations will include --autonomous in args. Continue to Core Loop.
• No: Set autonomous_mode = false. Skills are invoked without --autonomous (interactive mode). Continue to Core Loop.

On resume (--resume): If the state file contains "autonomous_mode": true, skip the consent prompt and continue in autonomous mode. Do not re-ask.

Step 2: Core State Machine Loop

This is the central orchestration logic. It runs after any entry handler has established or loaded state.

Loop algorithm:

1. Read loop context: Use Bash to read loop context via bash -c 'source .aod/scripts/bash/run-state.sh && aod_state_get_loop_context' — returns {stage}|{substage}|{stage_status} (e.g., plan|spec|in_progress). Parse the pipe-delimited result. Do NOT use aod_state_read here — the compound helper extracts only the 3 fields needed for routing.

2. Check completion: If stage_status from step 1 indicates all stages may be complete, verify by checking all 5 stage statuses via bash -c 'source .aod/scripts/bash/run-state.sh && aod_state_get_multi ".stages.discover.status" ".stages.define.status" ".stages.plan.status" ".stages.build.status" ".stages.deliver.status"'. If all show completed, MANDATORY: You MUST use the Read tool to load references/error-recovery.md, then follow the Lifecycle Complete instructions. Do NOT rely on memory of prior error-recovery content. If the file cannot be read, display an error and STOP.

3. Determine next stage: Use the current_stage and stage_status from step 1. If status is "completed", advance to the next stage in sequence: discover → define → plan → build → deliver

4. Handle Plan substages: If current_stage is plan, use the substage from step 1 and cycle through spec → project_plan → tasks. Only advance past Plan when all 3 substages complete. When advancing between substages, apply context boundary (see Plan Substage Tracking step 3a) to clear previous substage content and retain only approval metadata.

5. Write pre-stage checkpoint: Update state with current_stage status = "in_progress" and current timestamp. Write atomically via bash -c 'source .aod/scripts/bash/run-state.sh && aod_state_write '"'"'<json>'"'"''.

6. Display stage map: Show current progress (see Stage Map Display)

7. Display transition message: Show formatted header for the stage about to execute (see Transition Messages) 7a. Aggressive pre-Build boundary: If the stage about to execute is build, apply an extra-aggressive context boundary before invocation:

   1. Summarize all prior stages into a compact metadata block (~500 tokens max):
      • Feature: {feature_id} - {feature_name}
      • Branch: {branch}
      • Spec: {path} (APPROVED by PM)
      • Plan: {path} (APPROVED by PM + Architect)
      • Tasks: {path} (APPROVED by PM + Architect + Team-Lead)
      • Wave count: {N}
   2. Clear ALL prior stage content from working context
   3. Build skill reads its own context (tasks.md, plan.md, assignments) fresh
   4. Display: "[Pre-Build boundary] Prior stages summarized (~500 tokens). Build reads context fresh."

8. Invoke stage skill: Use the Skill tool to invoke the appropriate stage skill (see Stage Skill Mapping). Pass required context (idea text, issue number, artifact paths from prior stages).

9. Detect governance result: After the skill returns, first check the governance cache via bash -c 'source .aod/scripts/bash/run-state.sh && aod_state_get_governance_cache "{artifact}" "{reviewer}"'. If the cache returns a verdict (not "null"), use the cached result. If the cache returns "null", MANDATORY: You MUST use the Read tool to load references/governance.md before proceeding with governance gate detection. Do NOT rely on memory of prior governance content. If the file cannot be read, display an error and STOP. Follow the Governance Gate Detection and Governance Tier instructions from that file. Apply tier-specific rules.

   Parallel Triad Reviews: When a governance gate requires multiple reviewers (e.g., plan.md requires PM + Architect, tasks.md requires PM + Architect + Team-Lead), execute reviews in parallel using multiple Agent tool calls in a single message:

   1. Parallel execution: Launch all required reviewers simultaneously via Agent tool calls in one message. Each reviewer runs in its own agent context, preventing cross-contamination.
   2. Cache all verdicts: After all reviewers return, cache each verdict via aod_state_cache_governance before evaluating the aggregate result.
   3. Aggregate evaluation: After all reviewers complete, evaluate the combined result. If any reviewer returned CHANGES_REQUESTED or BLOCKED, handle per step 10 (use the most severe status).
   4. Same checklists and criteria: Parallel execution uses the same reviewers, review prompts, and approval criteria as sequential — only the execution model changes.

   Context note: Parallel reviews are safe with 1M context. Each reviewer runs in an isolated agent context, so there is no cross-reviewer drift. Re-grounding (see below) applies once after all reviewers return, not between each reviewer.

10. Handle result:

    • APPROVED / APPROVED_WITH_CONCERNS: Mark stage completed in state, record artifacts, write checkpoint, continue loop
    • CHANGES_REQUESTED: Follow the Rejection Handling instructions in references/governance.md (re-read if not already loaded). This includes Retry Tracking and Max-Retry Circuit Breaker checks.
    • BLOCKED: Follow the Blocked Handling instructions in references/governance.md (re-read if not already loaded).
    • No governance gate for this stage/tier: Mark completed, continue

11. Write post-stage checkpoint: Update state with completion status, artifacts, governance results, timestamp. Write atomically via bash -c 'source .aod/scripts/bash/run-state.sh && aod_state_write '"'"'<json>'"'"''. 11a. Apply context boundary (all stage transitions): When advancing from one stage to the next:

    1. Display: "[Context boundary] Clearing {completed_stage} context"
    2. Retain ONLY from the completed stage:
       • status (APPROVED / completed)
       • artifact_paths (list of file paths)
       • feature_id, github_issue, branch
       • governance verdict summary (one line per reviewer)
    3. The next stage skill will re-read any artifacts it needs via Read tool
    4. Skill file content from the completed stage is NOT carried forward

12. Update GitHub Issue label: If gh available, update stage label (see GitHub Integration)

13. Loop: Return to step 1

Re-grounding policy (context-thrifty): Re-read reference files only when variable-length output has been injected into context since the last read. This prevents template drift without wasting context on redundant reads.

• After governance reviews: If reviewer feedback, rejection details, or override justifications produced significant output (>50 lines), re-read references/governance.md before continuing the loop. With parallel reviews, this applies once after all reviewers return, since each reviewer runs in an isolated agent context.
• After rejection/blocked handling: Re-read references/governance.md before re-entering the loop, since user interaction and error display inject variable-length content.
• After lifecycle complete display: Re-read references/error-recovery.md to ensure the completion template is followed exactly.
• Skip re-grounding when: the previous step produced minimal output (stage map display, short status messages, cache hits). Unnecessary re-reads waste ~4-7K tokens each.

Stage sequence: discover → define → plan (spec → project_plan → tasks) → build → deliver

Note: aod.run orchestrates stages 1-5. Stage 6 (Document) is a separate human-driven command (/aod.document) run after Deliver. It is NOT part of this orchestrator.

Exit conditions:

• All stages completed → display lifecycle summary with /aod.document reminder
• BLOCKED with no resolution → save state, exit
• User chooses to pause → save state, exit
• Session ends → user resumes with --resume in new session

Plan Substage Tracking

The Plan stage contains 3 substages executed in strict sequence. The orchestrator tracks each substage independently and only advances past Plan when all 3 are complete.

Substage sequence: spec → project_plan → tasks

Algorithm (detailed expansion of Core Loop step 4):

1. When entering Plan stage: If current_substage is null, set it to spec (first substage). Update state: stages.plan.status = "in_progress", stages.plan.started_at = {now}, current_substage = "spec".

2. Determine active substage: Read current_substage from state. Check the substage's status in stages.plan.substages.{substage}.status:

   • If "completed": Advance to next substage in sequence
   • If "pending" or "in_progress": This is the active substage to execute

3. Substage advancement logic:

   • spec completed → set current_substage = "project_plan", set stages.plan.substages.project_plan.status = "in_progress". Apply context boundary (see step 3a).
   • project_plan completed → set current_substage = "tasks", set stages.plan.substages.tasks.status = "in_progress". Apply context boundary (see step 3a).
   • tasks completed → set current_substage = null, mark overall Plan stage as "completed", set stages.plan.completed_at = {now}

3a. Context boundary at substage transitions (FR-013, FR-014, FR-015, FR-016) — retained for context thrift; prevents accumulation even with 1M window:

When advancing from one substage to the next (spec → project_plan, or project_plan → tasks), apply a context boundary to prevent context accumulation:

Step 1 - Display boundary message:

[Context boundary] Clearing {previous_substage} context

Where {previous_substage} is spec or project_plan.

Step 2 - Extract and retain only approval metadata: From the completed substage, retain only:

• status: The approval status (e.g., "APPROVED")
• artifact_path: Path to the artifact (e.g., specs/{NNN}-*/spec.md)
• feature_id: The 3-digit feature ID (e.g., "047")

These values are already persisted in run-state.json under stages.plan.substages.{substage} and do not require re-extraction.

Step 3 - Clear previous substage full content: The previous substage's artifact content (spec.md or plan.md full text) is NOT carried forward. The next substage skill will read its own required context fresh.

Step 4 - On-demand re-read available: If the next substage explicitly needs details from a prior artifact, it can re-read the artifact using the path stored in metadata. This is NOT automatic — the substage skill must explicitly invoke the Read tool with the artifact path from stages.plan.substages.{prior_substage}.artifacts.

Example boundary output:

[Context boundary] Clearing spec context
Retained metadata: {status: "APPROVED", artifact_path: "specs/047-*/spec.md", feature_id: "047"}

4. Write substage checkpoint: After each substage transition, write state atomically. This ensures that if the session dies between substages, the orchestrator can resume at the correct substage.

5. Skill invocation per substage:

   • spec substage → invoke aod.spec skill
   • project_plan substage → invoke aod.project-plan skill
   • tasks substage → invoke aod.tasks skill

6. Governance per substage: Each substage has its own governance gate. First check the governance cache via aod_state_get_governance_cache (see Core Loop step 9). If the cache returns "null", fall back to reading the substage's artifact frontmatter (load references/governance.md for the detection algorithm):

   • spec: Check specs/{NNN}-*/spec.md for PM sign-off
   • project_plan: Check specs/{NNN}-*/plan.md for PM + Architect sign-off
   • tasks: Check specs/{NNN}-*/tasks.md for PM + Architect + Team-Lead sign-off

7. Display: When displaying the stage map during Plan, show the active substage:

   [>] Plan (spec)       — spec substage in progress
   [>] Plan (plan)       — project_plan substage in progress
   [>] Plan (tasks)      — tasks substage in progress
   

Stage Skill Mapping

Each lifecycle stage maps to an existing AOD skill invoked via the Skill tool. The orchestrator delegates all stage work — it never re-implements stage logic.

Invocation pattern: Use the Skill tool with skill: "{skill_name}" and pass arguments as args: "{arguments}".

Context passing between stages (FR-012):

• After Discover completes: extract GitHub Issue number from discovery output; store in state as github_issue
• After Define completes: PRD path is at docs/product/02_PRD/{NNN}-*.md; store in state artifacts
• After Plan:spec completes: spec path is at specs/{NNN}-*/spec.md; store in state artifacts
• After Plan:project_plan completes: plan path is at specs/{NNN}-*/plan.md; store in state artifacts
• After Plan:tasks completes: tasks path is at specs/{NNN}-*/tasks.md; store in state artifacts
• After Build completes: implementation files tracked via tasks.md [X] markers
• After Deliver completes: delivery summary and metrics captured

Argument formatting per stage:

When autonomous_mode == true, prepend --autonomous to all skill args:

• Discover: args: "--autonomous {idea_text}" — pass flag + raw idea description
• Define: args: "--autonomous {feature_title}" — pass flag + feature title/topic
• Plan stages: args: "--autonomous" — flag only; skills read context from branch
• Build: args: "--orchestrated --autonomous" — both flags enable orchestrated + autonomous modes
• Deliver: args: "--autonomous FEATURE: {NNN} - {feature_name}" — flag + feature info

When autonomous_mode == false (interactive), omit --autonomous:

• Discover: args: "{idea_text}"
• Define: args: "{feature_title}"
• Plan stages: no args
• Build: args: "--orchestrated"
• Deliver: args: "FEATURE: {NNN} - {feature_name}"

Post-Stage Context Extraction

After each stage skill returns, the orchestrator extracts context from the produced artifacts and updates the state file. This ensures subsequent stages receive the correct inputs.

After Discover completes:

1. The Discover skill creates a GitHub Issue and outputs the issue number. Read the orchestration output to find the issue number.
2. Use Bash to scan for new GitHub Issues: gh issue list --label "stage:discover" --json number,title --limit 5 (if gh available)
3. Update state fields:
   • github_issue: Set to the issue number
   • feature_id: Zero-pad the issue number to 3 digits (e.g., 22 → "022")
   • branch: Set to {feature_id}-{feature_name} (e.g., "022-add-dark-mode-toggle")
4. Create the feature branch if not already on it: git checkout -b {branch} (or confirm current branch matches)
5. Record artifacts: Add the GitHub Issue URL to stages.discover.artifacts
6. Write updated state atomically

After Define completes:

1. Use Glob to find the PRD: docs/product/02_PRD/{NNN}-*.md where NNN is feature_id
2. Record artifacts: Add the PRD path to stages.define.artifacts
3. Write updated state atomically

After Plan:spec completes:

1. Use Glob to find the spec: specs/{NNN}-*/spec.md
2. Record artifacts: Add the spec path to stages.plan.substages.spec.artifacts
3. Write updated state atomically

After Plan:project_plan completes:

1. Use Glob to find the plan: specs/{NNN}-*/plan.md
2. Record artifacts: Add the plan path to stages.plan.substages.project_plan.artifacts
3. Write updated state atomically

After Plan:tasks completes:

1. Use Glob to find tasks and assignments: specs/{NNN}-*/tasks.md, specs/{NNN}-*/agent-assignments.md
2. Record artifacts: Add paths to stages.plan.substages.tasks.artifacts
3. Mark overall Plan stage as completed
4. Write updated state atomically

After Plan:tasks completes (continued) — Size Estimation Display:

After recording Plan:tasks artifacts and before the Core Loop advances to Build, perform a size estimation:

1. Read agent-assignments.md from specs/{NNN}-*/agent-assignments.md

2. Count the number of waves (sections labeled "Wave 1", "Wave 2", etc.)

3. Apply the heuristic:

   • wave_count <= 3 → session_strategy = "one-shot", estimated_sessions = 1
   • wave_count <= 6 → session_strategy = "cautious", estimated_sessions = 2
   • wave_count > 6 → session_strategy = "multi-session", estimated_sessions = ceil(wave_count / 3)

4. Update state with the estimation:

   bash -c 'source .aod/scripts/bash/run-state.sh && aod_state_write '"'"'{"session_strategy":"{strategy}","estimated_sessions":{N},"build_progress":{"total_waves":{wave_count},"completed_waves":0,"session_breaks":[]}}'"'"''
   

5. Display the build estimate:

   --- BUILD ESTIMATE ---
   Waves: {wave_count}
   Estimated sessions: {estimated_sessions}
   
   {If wave_count <= 3: "Expected to complete in this session."}
   {If wave_count > 3: "May require ~{estimated_sessions} sessions. The orchestrator will auto-break and resume if needed."}
   

After Build completes:

1. Read tasks.md from specs/{NNN}-*/tasks.md
2. Count total tasks (lines matching - [ ] or - [X])
3. Count completed tasks (lines matching - [X])
4. Determine the last completed wave by reading agent-assignments.md and cross-referencing completed tasks
5. If completed < total (session break protocol):
   • Parse the AOD_BUILD_RESULT comment from build output
   • Log in error_log with type "build_incomplete" and message including wave progress
   • Update build_progress in state:

     bash -c 'source .aod/scripts/bash/run-state.sh && aod_state_write '"'"'{"build_progress":{"total_waves":{total},"completed_waves":{N},"session_breaks":[{"session":{session_count},"waves_completed":"{range}","timestamp":"{now}"}]}}'"'"''
     

   • Log the session break decision to autonomous_decisions:

     bash -c 'source .aod/scripts/bash/run-state.sh && aod_state_append ".autonomous_decisions" '"'"'{"decision":"session_break","reason":"Build incomplete: {completed}/{total} tasks after wave {N}","timestamp":"{now}"}'"'"''
     

   • Display the session break message:

     AOD ORCHESTRATOR — Session Break
     ==================================
     Feature: {feature_name} (#{github_issue})
     Build: Wave {N}/{total_waves} complete ({completed_tasks}/{total_tasks} tasks)
     
     The remaining waves require a new conversation.
     
     To continue:
       /aod.run --resume
     
     The orchestrator will pick up from Wave {N+1} automatically.
     
     Resume prompt (copy-paste):
       claude "Resume aod.run for #{github_issue} — {feature_name}. Run /aod.run --resume"
     

   • STOP — Do NOT continue to Deliver. Exit the Core Loop.
6. If completed == total: Mark Build as completed, continue to Deliver
7. Record artifacts: Add "tasks.md (all tasks completed)" to stages.build.artifacts
8. Write updated state atomically

After Deliver completes:

1. The deliver stage produces a delivery summary and may update GitHub Issue to stage:done
2. Record artifacts: Add "delivery complete" to stages.deliver.artifacts
3. Write updated state atomically
4. MANDATORY: You MUST use the Read tool to load references/error-recovery.md, then follow the Lifecycle Complete instructions. If the file cannot be read, display an error and STOP.

Stage Map Display

Display the stage map after each stage transition to show progress. This is referenced by Core Loop step 6.

Algorithm:

1. Read state from .aod/run-state.json
2. For each stage in sequence (discover, define, plan, build, deliver), determine its display marker:
   • status == "completed" → [x]
   • status == "in_progress" → [>]
   • status == "pending" → [ ]
   • status == "failed" → [!]
3. For the Plan stage, append the active substage in parentheses if in progress:
   • If current_substage == "spec" → Plan (spec)
   • If current_substage == "project_plan" → Plan (plan)
   • If current_substage == "tasks" → Plan (tasks)
   • If Plan is completed → Plan
4. Display the formatted stage map:

Stage Map:
  {marker} Discover  {marker} Define  {marker} Plan{substage}  {marker} Build  {marker} Deliver

Examples:

Starting a new lifecycle:

Stage Map:
  [>] Discover  [ ] Define  [ ] Plan  [ ] Build  [ ] Deliver

After Discover and Define complete, Plan:spec in progress:

Stage Map:
  [x] Discover  [x] Define  [>] Plan (spec)  [ ] Build  [ ] Deliver

Mid-lifecycle with Build in progress:

Stage Map:
  [x] Discover  [x] Define  [x] Plan  [>] Build  [ ] Deliver

All stages complete:

Stage Map:
  [x] Discover  [x] Define  [x] Plan  [x] Build  [x] Deliver

Remaining: /aod.document (manual)

Transition Messages

Display a formatted transition header before each stage begins executing. This is referenced by Core Loop step 7.

Algorithm (called by Core Loop step 7, before each stage skill invocation):

1. Read current state: Get current_stage and current_substage from state.

2. Map stage to number and detail: Use the lookup table below:

   current_stage	current_substage	N	STAGE_NAME	Substage Detail
   discover	null	1	DISCOVER	—
   define	null	2	DEFINE	—
   plan	spec	3	PLAN	sub-stage 1/3: Feature Specification
   plan	project_plan	3	PLAN	sub-stage 2/3: Architecture Plan
   plan	tasks	3	PLAN	sub-stage 3/3: Task Breakdown
   build	null	4	BUILD	—
   deliver	null	5	DELIVER	—

3. Format and display:

   For non-Plan stages:

   --- STAGE {N}: {STAGE_NAME} ---
   

   For Plan substages:

   --- STAGE 3: PLAN ({substage detail}) ---
   

Examples:

--- STAGE 1: DISCOVER ---
--- STAGE 3: PLAN (sub-stage 1/3: Feature Specification) ---
--- STAGE 4: BUILD ---

GitHub Integration

After each stage completes successfully (governance gate passed), update the GitHub Issue's stage:* label to reflect the new current stage. This keeps the GitHub Issue board in sync with the orchestration state (FR-023).

Algorithm (called by Core Loop step 12, after post-stage checkpoint):

1. Check prerequisites:

   • Read github_issue from state. If null (no GitHub Issue for this feature), skip entirely.
   • Check if gh CLI is available: command -v gh >/dev/null 2>&1. If not, skip silently.
   • Check if gh is authenticated: gh auth status >/dev/null 2>&1. If not, skip silently.

2. Determine the new stage label: Map the newly-completed stage to the next stage in the sequence:

   Completed Stage	Completed Substage	New Label
   discover	—	stage:define
   define	—	stage:plan
   plan	spec	stage:plan (still in Plan)
   plan	project_plan	stage:plan (still in Plan)
   plan	tasks	stage:build
   build	—	stage:deliver
   deliver	—	stage:done

   Note: Plan substage completions (spec, project_plan) do not change the label — the issue stays at stage:plan until all 3 substages complete.

3. Update the label: Use the github-lifecycle.sh function:

   bash -c 'source .aod/scripts/bash/github-lifecycle.sh && aod_gh_update_stage {github_issue} {new_stage}'
   

4. Handle failures gracefully: If the label update fails, log a warning but do NOT halt orchestration.

   • Display: "Note: GitHub label update skipped ({reason}). Orchestration continues."

5. Backlog refresh: After updating the label:

   bash .aod/scripts/bash/backlog-regenerate.sh 2>/dev/null || true
   

   This is fire-and-forget — failure does not affect orchestration.

Error Logging

Capture stage errors and significant events in the state file's error_log array for debugging and auditability. Error entries follow Entity 4 schema.

Algorithm (called whenever an error or significant event occurs during orchestration):

1. Build error entry:

{
  "timestamp": "{current ISO 8601 timestamp}",
  "stage": "{current_stage}",
  "type": "{error_type}",
  "message": "{descriptive error message}",
  "recoverable": true
}

2. Error types (standardized values for type field):

   Type	When Used	Recoverable
   stage_error	A stage skill invocation fails or returns an error	true
   governance_rejection	A governance gate returns CHANGES_REQUESTED	true
   governance_blocked	A governance gate returns BLOCKED	true
   circuit_breaker	Max retries (3) reached on a governance gate	true
   user_abort	User chose to abort orchestration	true
   artifact_missing	Artifact recorded in state not found on disk	true
   state_corruption	State file failed validation	true
   github_error	GitHub CLI operation failed	true
   skill_invocation_error	Skill tool invocation returned unexpected result	true

3. Append to state: Use the aod_state_append function:

   bash -c 'source .aod/scripts/bash/run-state.sh && aod_state_append ".error_log" '"'"'{"timestamp":"...","stage":"...","type":"...","message":"...","recoverable":true}'"'"''
   

4. When to log errors:

   • Stage skill failure: When a Skill tool invocation produces an error or unexpected output
   • Governance gate rejection: Also tracked in gate_rejections, log summary in error_log
   • Circuit breaker activation: When max retries are reached
   • User abort: When the user chooses to abort
   • Artifact inconsistency: When resume validation detects missing artifacts
   • State corruption: When the state file fails validation
   • GitHub errors: When gh CLI operations fail

5. Error entries are append-only: Never remove or modify existing error log entries. The log provides a chronological audit trail.

   Type	When Used	Recoverable
   build_incomplete	Post-build verification finds incomplete tasks	true

Adaptive Session Management

The orchestrator adapts its session strategy based on feature size. Small features complete in one session; large features automatically split across sessions when context runs out.

Size Estimation Heuristic (executed after Plan:tasks completes, before Build):

wave_count = count of waves in agent-assignments.md

if wave_count <= 3:
  session_strategy = "one-shot"
  estimated_sessions = 1
elif wave_count <= 6:
  session_strategy = "cautious"
  estimated_sessions = 2
else:
  session_strategy = "multi-session"
  estimated_sessions = ceil(wave_count / 3)

Session breaks are reactive, not predictive: Token heuristics don't work — Claude Code doesn't expose token usage to skills. Instead, aod.build runs waves until either all complete (AOD_BUILD_RESULT:COMPLETE) or context degrades (AOD_BUILD_RESULT:PARTIAL). Post-build verification in the orchestrator then triggers a session break if tasks remain incomplete.

State fields for session management:

Resume-after-break flow: When aod.run --resume loads a state where Build is in_progress, it re-invokes aod.build --orchestrated --autonomous. Build's Step 1.6 detects completed waves via [X] markers and continues from the next incomplete wave. This repeats (recursive session breaks) until all waves complete, then the orchestrator advances to Deliver.

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