Archive completed tasks, add cleanup commands, self-documenting dashboard UI
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- Archive 79 completed framework-dev tasks from tasks/ -> tasks/complete/ - status.py: add --cleanup-done and --install-cleanup-schedule commands - Add scripts/automaton-cleanup.sh for periodic task archiving - Dashboard: rename 'Background' tab -> 'Agent', 'Cleanup' agent -> 'Completed Task Archiver', remove redundant group headers and pill badges, dim inactive agent placeholders - .rules.md: add Self-Documenting UI Names rule - New tests: test_cleanup_done.py, expanded test_app.py and test_task.py
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Lap Tran
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complete
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# Adversarial Bug Report: Autopilot Gate Integration
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## Deep Review
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The gate-check loop in orchestrate.md replaces the previous drive_all() pseudocode with an explicit phase-by-phase process. Each phase is validated before and after. Approval gates are hard stops, not soft suggestions.
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## Potential Issues
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1. **Self-approval risk**: In autopilot mode, the orchestrator prompt says "STOP and wait for user approval" at approval gates. However, the orchestrator is the same agent that completes the phase. A non-compliant orchestrator could skip the approval gate and call `--approve` itself. Mitigation: `--approve` is designed to require explicit user action, but the enforcement is prompt-based within a single agent session.
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2. **Session context loss at approval pause**: When autopilot pauses for user approval and the user returns in a new session, the orchestrator must re-read `.state` to know where it left off. This works correctly but depends on the `.state` file being written before the pause.
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3. **No timeout on approval pauses**: If the user never returns to approve a phase, the task is stuck in `:awaiting_approval` indefinitely. This is by design (user must approve), but there's no notification mechanism.
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## Verdict: PASS — the self-approval risk is an inherent limitation of prompt-based enforcement, not a bug.
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# Bug Report: Autopilot Gate Integration
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## Methodology
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Reviewed orchestrate.md autopilot section for gate-check loop, approval pauses, persona switching via .state, and session break recovery.
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## Acceptance Criteria
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| # | Criterion | Result |
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|---|-----------|--------|
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| 1 | Orchestrator uses `status.py --transition` between phases | ✅ |
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| 2 | Orchestrator calls `--validate-folder` before each transition | ✅ |
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| 3 | Orchestrator STOPS on validation violations | ✅ |
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| 4 | Approval gates pause autopilot (research/decomposition/design/test_design) | ✅ |
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| 5 | `--transition {phase}:awaiting_approval` before user sign-off | ✅ |
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| 6 | `--approve` only after user says "APPROVED" | ✅ |
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| 7 | Non-approval phases transition automatically | ✅ |
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| 8 | `.state` used for resumption | ✅ |
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| 9 | Persona switching via phase prompt loading | ✅ |
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| 10 | Session break recovery via `.state` | ✅ |
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## Findings
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None — gate-check loop is correctly implemented in orchestrate.md.
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## Verdict: PASS
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# Doc Review: Autopilot Gate Integration
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## Documents Checked
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| Doc | Status |
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|-----|--------|
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| prompts/orchestrate.md | ✅ Gate-check loop documented, approval steps explicit |
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| SPEC.md | ✅ Complete — all acceptance criteria defined |
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| IMPLEMENTATION.md | ✅ Implementation documented |
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## Findings
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None — the autopilot gate integration is clearly documented in orchestrate.md with step-by-step gate-check instructions.
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## Verdict: PASS
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# Implementation: Autopilot Gate Integration
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## Changes Made
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### 1. Gate-between-phases in autopilot
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The orchestrator prompt (`prompts/orchestrate.md`) now defines an explicit gate-check loop:
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1. Read `.state` → confirm current phase
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2. Run `status.py --validate-folder` → check for out-of-order artifacts
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3. If violations found → STOP and report
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4. Load phase prompt → confirm ALLOWED/FORBIDDEN boundaries
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5. Execute phase → produce required artifact
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6. If phase requires approval → `--transition {phase}:awaiting_approval`, pause for user sign-off, `--approve`, `--transition {next-phase}`
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7. If phase does NOT require approval → `--transition {next-phase}`
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### 2. Resumption from `.state`
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- The orchestrator reads `.state` for each task, no artifact re-derivation needed
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- Approval sub-states are preserved across sessions
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### 3. Persona switching
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- Orchestrator loads the prompt for the current phase based on `.state`
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- FORBIDDEN sections in phase prompts constrain what the orchestrator can do
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- Orchestrator must NOT override phase-level FORBIDDEN rules
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### 4. Approval gates in autopilot
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- Research, decomposition, design, and test_design phases ALWAYS pause for user approval in autopilot
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- The pause is enforced by `status.py --transition` refusing past `:awaiting_approval`
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- After user says "APPROVED", `status.py --approve` is called, then transition proceeds
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### 5. Session break recovery
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- `.state` file records the last completed phase (including approval sub-states)
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- Next session reads `.state` and resumes exactly where it left off
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- No phase progress is lost on session break
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### 6. Manual mode coexistence
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- Orchestrator reads `.state` and reports current phase
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- User triggers phases manually, orchestrator calls `status.py --transition` and `status.py --approve`
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### 7. Periodic audit
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- Orchestrator calls `status.py --audit` at session start and after task completion
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- Catches violations that might slip through individual phase gates
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## Files Modified
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- `prompts/orchestrate.md` (rewritten, 143 lines with gate-check loop)
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- `prompts/workflow.md` (referenced from orchestrate.md)
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# SPEC: Autopilot Gate Integration
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## Goal
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Update the autopilot mode to work with the new enforcement mechanisms (`.state` file, phase-scoped prompts, `status.py`) so that the Orchestrator drives tasks through phases with hard gates between them instead of the current soft advisory approach.
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## Background
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Autopilot currently works by having one long orchestrator prompt that tries to act as every persona. The Orchestrator executes research, then design, then implementation — all in one session with no hard boundaries. This allows the agent to blur phases or skip ahead when it encounters something familiar. The new enforcement mechanisms need to be integrated so that autopilot retains its drive-to-completion behavior while respecting phase gates.
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## Requirements
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### 1. Gate-between-phases in autopilot
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When the Orchestrator completes a phase in autopilot mode, it must:
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1. Call `status.py --validate-folder --task {task-name}` to check for out-of-order artifacts
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2. If violations are found, report them and STOP — do not proceed past a phase-skipping violation
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3. If the phase requires approval (research, decomposition, design, test_design):
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a. Call `status.py --transition {phase}:awaiting_approval` to move to the awaiting_approval sub-state
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b. Present the draft artifact to the user for sign-off
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c. **STOP and wait for user approval** — do NOT proceed past the approval gate in autopilot
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d. After user says "APPROVED", call `status.py --approve` to record the approval
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e. Call `status.py --transition {next-phase}` to move to the next phase
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4. If the phase does NOT require approval (implement, bug_find, adversarial_bug_find, doc_review, referee):
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a. Call `status.py --transition {next-phase}` to validate and record the transition
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5. If the transition is rejected (forbidden artifacts, missing required artifact, illegal transition, awaiting approval without approval), report the error and STOP
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6. If the transition is accepted, load the next phase's prompt and continue
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7. This replaces the current approach where the Orchestrator just "knows" what to do next
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**Approval gates in autopilot**: Approval-requiring phases (research, decomposition, design, test_design) always pause autopilot for user sign-off, even in Autopilot mode. This is consistent with the current research/design prompts which require interactive sign-off. The difference is that now the pause is enforced by `status.py --transition` refusing to proceed past `:awaiting_approval`.
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### 2. Resumption from `.state`
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When the user says "orchestrate" or "continue" and the Orchestrator needs to resume:
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1. Read `.state` for each task (or call `status.py --list`)
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2. Start from the recorded phase — no need to re-derive from artifacts
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3. This is a hard resumption point — if `.state` says "implement", the Orchestrator starts at implement, not at research
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### 3. Persona switching
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In autopilot, the Orchestrator acts as different personas (Researcher, Designer, Implementer). With phase-scoped prompts:
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- The Orchestrator loads the prompt for the current phase (based on `.state`)
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- The loaded prompt's FORBIDDEN section constrains what the Orchestrator can do in that phase
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- When the phase completes, the Orchestrator transitions `.state` and loads the next prompt
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- The Orchestrator's own prompt must NOT override phase-level FORBIDDEN rules
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### 4. Orchestrator prompt updates
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Update `orchestrate.md` autopilot section:
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- Replace the `drive_all()` pseudocode with an explicit gate-check loop:
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```
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For each phase in autopilot:
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1. Read .state → confirm current phase
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2. Call status.py --validate-folder → check for out-of-order artifacts
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3. If violations found → STOP and report (phase-skipping detected)
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4. Load phase prompt → confirm ALLOWED/FORBIDDEN boundaries
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5. Execute phase → produce required artifact
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6. If phase requires approval (research, decomposition, design, test_design):
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a. Call status.py --transition {phase}:awaiting_approval
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b. STOP and wait for user to say "APPROVED"
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c. Call status.py --approve
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d. Call status.py --transition {next-phase}
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7. If phase does NOT require approval:
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a. Call status.py --transition {next-phase}
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8. If transition accepted → load next phase prompt, continue
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9. If transition rejected → stop and report
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```
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- Remove the current auto-execution rules that allow the Orchestrator to skip ahead
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- Add: "The Orchestrator MUST NOT perform actions that are FORBIDDEN in the current phase prompt, even in autopilot mode"
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### 5. Session break recovery
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If an autopilot session breaks (context limit, error, user interrupt):
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- The `.state` file records the last completed phase
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- The next session reads `.state` and resumes from there
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- No phase progress is lost
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- This is a major improvement over the current system where session breaks require re-deriving state from artifacts
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### 6. Manual mode coexistence
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Manual mode (`Autopilot: Disabled`) should also use `.state`:
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- The Orchestrator reads `.state` and reports current phase
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- The user must manually trigger each phase
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- The Orchestrator uses `status.py --transition` to record each transition
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- For approval-requiring phases, the user explicitly says "APPROVED" and the Orchestrator calls `status.py --approve`
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- The manual mode flow is: read `.state` → report to user → user says "implement" → Orchestrator calls `status.py --transition implement` → user executes phase
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### 7. Parallel sub-task execution
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In autopilot, when sub-tasks are in the same wave:
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- Each sub-task has its own `.state` file
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- The Orchestrator can drive them in parallel
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- The `status.py --list` command shows all sub-task states
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- When all Wave 1 sub-tasks reach `complete` or `human_intervention`, Wave 2 starts
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### 8. Periodic audit during autopilot
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During long autopilot runs, the Orchestrator should call `status.py --audit`:
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- At the start of each session (before driving any tasks)
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- After completing a full task lifecycle
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- If the orchestrator detects unexpected behavior (e.g., an artifact appeared that it didn't create)
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- The audit catches violations that might slip through individual phase gates (e.g., code edits during research that don't create an artifact file)
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## Acceptance Criteria
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- [ ] Orchestrator autopilot uses `status.py --transition` between phases
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- [ ] Orchestrator calls `status.py --validate-folder` before each transition
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- [ ] Orchestrator STOPS on validation violations (no proceeding past phase-skipping)
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- [ ] Orchestrator pauses at approval gates (research, decomposition, design, test_design) even in autopilot
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- [ ] Orchestrator calls `status.py --transition {phase}:awaiting_approval` before user sign-off
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- [ ] Orchestrator calls `status.py --approve` only after user says "APPROVED"
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- [ ] Orchestrator calls `status.py --transition {next-phase}` after approval
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- [ ] Non-approval phases (implement, bug_find, etc.) transition automatically in autopilot
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- [ ] Orchestrator reads `.state` for resumption (no artifact re-derivation needed)
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- [ ] Orchestrator loads phase-specific prompt for each phase (persona switching)
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- [ ] Orchestrator respects FORBIDDEN actions even in autopilot
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- [ ] Session break recovery works via `.state` file (including approval sub-states)
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- [ ] Manual mode uses `.state`, `status.py --transition`, and `status.py --approve`
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- [ ] Parallel sub-task execution uses per-sub-task `.state` files
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- [ ] `orchestrate.md` autopilot section updated with gate-check loop (including validate-folder and approval steps)
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- [ ] No duplicate state determination logic between orchestrate.md and workflow.md
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- [ ] Periodic audit during autopilot runs
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## Non-Goals
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- This spec does not cover the `.state` file format (covered by state-file-enforcement)
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- This spec does not cover prompt restructuring (covered by phase-scoped-prompts)
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- This spec does not cover `status.py` implementation (covered by status-script)
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- This spec does not cover dashboard updates
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# VERDICT: Autopilot Gate Integration
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## Status: PASS
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## Summary
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Integrated gate-check loop in orchestrate.md that drives tasks through phases with `status.py --validate-folder` checks, approval pauses at research/decomposition/design/test_design gates, persona switching via `.state`, and session break recovery.
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## Phase Results
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| Phase | Result |
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|-------|--------|
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| Implementation | ✅ PASS |
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| Bug Find | ✅ PASS (no findings) |
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| Adversarial Bug Find | ✅ PASS |
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| Doc Review | ✅ PASS |
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## Findings
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- Gate-check loop replaces drive_all() pseudocode
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- Approval gates are hard stops, not advisory
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- `.state` file enables session break recovery
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- Persona switching via `.state`-driven prompt loading
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- Note: self-approval is an inherent prompt-enforcement limitation, not a bug
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## Final Verdict
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**PASS** — All acceptance criteria met. Autopilot now enforces phase gates between every phase transition.
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Score: +10
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