fusion/docs/missions.md

Missions

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Missions provide structured planning across multiple related tasks.

Roadmaps are a separate lightweight planning model (Roadmap → RoadmapMilestone → RoadmapFeature) used for standalone planning. Missions remain the richer execution-oriented hierarchy when you need slice activation, autopilot, and feature-to-task delivery tracking.

Mission Hierarchy

Fusion models delivery as:

Mission → Milestone → Slice → Feature → Task

Example:

Mission: Improve Reliability
  Milestone: Stabilize execution pipeline
    Slice: Retry and recovery hardening
      Feature: Stuck task recovery improvements
        Task: FN-210
        Task: FN-214

Creating Missions

Dashboard

Use the Mission Manager UI to create missions and build hierarchy interactively.

On mobile, Mission Manager surfaces the primary Plan New Mission CTA at the top of the mission list for faster access, while desktop keeps the split-layout sidebar CTA anchored in the bottom action region as the primary entry point.

CLI

fn mission create "Reliability initiative" "Reduce execution failures and improve recovery"
fn mission list
fn mission show mission_123
fn mission activate-slice slice_456
fn mission delete mission_123 --force

Mission Interview and Planning Workflow

The dashboard supports mission planning workflows where you can:

• Define mission outcomes
• Break work into milestones/slices/features
• Associate features to executable tasks
• Track progress at each layer
• Persisted missions with interviewState: "in_progress" remain visible as interview-styled mission cards in the main mission list so planning work does not disappear after reloads
• Resume in-progress mission interview sessions directly from separate transient session rows in the main missions list (mission_interview sessions in generating, awaiting_input, or error) before a mission record is created
• Banner-driven mission interview resumes are one-shot: if you close or send the interview to background, Missions re-fetches project-scoped mission_interview sessions and re-surfaces the transient row (including on the mobile stacked Missions view) so resume/retry remains discoverable without losing persisted interviewState: "in_progress" mission cards

Mission Interview Drafts

Mission interview sessions are persisted in ai_sessions before a mission row exists, so unfinished drafts stay recoverable across reloads and restarts.

• Dashboard: the Missions view shows a Drafts section for in-flight mission_interview sessions with Resume and Discard actions.
• CLI: fn mission list shows drafts by default before normal mission status sections. Pass --no-drafts to hide them.
• pi extension: fn_mission_list includes drafts by default and accepts includeDrafts: false to suppress them.
• Discarding drafts: discarding removes the ai_sessions row even for cold drafts after a server restart.

Mission interview draft endpoints:

Endpoint	Purpose
GET /api/missions/interview/drafts	List in-flight mission interview drafts
POST /api/missions/interview/drafts/:sessionId/discard	Discard a draft session

Auto-Generated Assertions

When missions are created through the interview planning workflow, Fusion automatically generates contract assertions for each feature:

• Assertion text source priority: acceptanceCriteria → feature.description → fallback text ("Verify implementation of: {feature.title}")
• Assertions are linked to features: Each auto-generated assertion is automatically linked to its feature, enabling mission validation rollup and enriched planning context
• Verification fields: Milestone and slice verification criteria from the interview are stored in dedicated verification fields rather than concatenated into descriptions
• Partial plans handled: Auto-generation is robust to partial plans (missing slices/features or empty criteria) without throwing errors

Slice Activation and Progress

Slices represent staged execution windows.

• Pending slices remain inactive
• Active slices are currently allowed to progress
• Completion rolls up through feature → slice → milestone → mission

Manual activation is available through fn mission activate-slice <slice-id>.

Mission Autopilot

When autopilotEnabled is on, Fusion can watch completion events and progress missions automatically.

State machine:

• inactive
• watching
• activating
• completing

Typical flow:

1. Mission is watched
2. Task completion updates feature status
3. If a slice is complete, autopilot activates next pending slice
4. When milestones are all complete, mission transitions to complete

autopilotEnabled vs autoAdvance

• autopilotEnabled: primary control for autopilot behavior — enables background monitoring, orchestration, and automatic slice activation when a slice completes. Also triggers auto-planning (converting features to tasks) when a slice is activated.
• autoAdvance: legacy fallback for backward compatibility with existing mission data. Kept for compatibility — new missions should use autopilotEnabled.

Auto-planning behavior:

• autopilotEnabled=true → features in activated slices are automatically planned (converted to tasks)
• autopilotEnabled=false, autoAdvance=true → features are planned (legacy compat)
• autopilotEnabled=false, autoAdvance=false → manual slice activation only

Slice progression (on slice completion):

• autopilotEnabled=true → next pending slice is automatically activated
• autopilotEnabled=false, autoAdvance=true → next pending slice is activated (legacy compat)
• autopilotEnabled=false, autoAdvance=false → manual activation required

Dashboard UI: The Mission Manager shows autopilotEnabled as the primary control. When enabling autopilot on an already-active mission, the system automatically checks whether recovery is needed (no active slice or completed active slice) and progresses accordingly.

Autopilot API Endpoints

Endpoint	Purpose
GET /api/missions/:missionId/autopilot	Get autopilot status for mission
PATCH /api/missions/:missionId/autopilot	Enable/disable autopilot ({ enabled: boolean })
POST /api/missions/:missionId/autopilot/start	Start watching manually
POST /api/missions/:missionId/autopilot/stop	Stop watching manually

Validation Contract Lifecycle

Fusion's validation contract lifecycle is the structured feature delivery system for missions. It combines validation contracts, AI validation, and bounded retries to provide systematic, auditable feature completion. The lifecycle covers the full end-to-end path from clarification through blocked handoff.

End-to-End Flow

Clarification → Validation Contract → Feature Execution → Validator Loop
      ↑                                                         ↓
      │    Fix-Feature Retry ←─ (budget exhausted?) ←───────────┘
      │
Blocked Handoff ←── (budget exhausted, root cause unresolvable)

Phase 1: Clarification

The clarification phase occurs during mission interview and planning. Operators define:

• Milestone outcomes and slice verification criteria stored in dedicated verification fields
• Feature descriptions and acceptance criteria

These inputs flow directly into assertion auto-generation in the next phase.

Phase 2: Validation Contract

Contract assertions (MissionContractAssertion) formalize what must be true for a feature to be considered complete:

interface MissionContractAssertion {
  id: string;              // e.g., "CA-A3B7CD-E9F2"
  milestoneId: string;     // Parent milestone
  title: string;           // Human-readable title
  assertion: string;       // Behavioral plan
  status: AssertionStatus; // pending | passed | failed | blocked
  orderIndex: number;      // Sort order within milestone
  featureIds: string[];    // Linked features (many-to-many)
}

Assertion text source priority:

1. acceptanceCriteria (from feature planning)
2. feature.description (fallback)
3. Fallback text: "Verify implementation of: {feature.title}"

Coverage tracking: MilestoneValidationRollup computes per-milestone coverage:

interface MilestoneValidationRollup {
  milestoneId: string;
  totalAssertions: number;
  passed: number;
  failed: number;
  blocked: number;
  pending: number;
  unlinked: number;
  state: MilestoneValidationState;
}

Validation state precedence (highest priority wins):

1. not_started — no assertions exist
2. needs_coverage — assertions exist but some are not linked to features
3. ready — assertions exist and are linked, but not all have passed
4. passed — all assertions have passed
5. failed — at least one assertion failed
6. blocked — at least one assertion is blocked

Phase 3: Feature Execution Loop

Features track their implementation state via FeatureLoopState separate from task status:

type FeatureLoopState =
  | "idle"         // Not yet started
  | "implementing" // Tasks are in-flight
  | "validating"   // Awaiting AI validation
  | "needs_fix"    // Validation failed, retry in progress
  | "passed"       // All assertions passed
  | "blocked";     // Retry budget exhausted, cannot proceed

State transitions:

idle → implementing → validating → passed (all assertions pass)
                          ↓
                   needs_fix → implementing (retry feature created)
                          ↓
                      blocked (budget exhausted)

When a feature enters the implementing state, implementationAttemptCount is initialized and incremented on each retry.

Phase 4: Validator Loop

On task completion, the scheduler calls MissionExecutionLoop.processTaskOutcome() to run AI validation:

1. Find the feature linked to the completed task
2. Transition feature to validating state
3. Fire AI validator agent against contract assertions
4. Record MissionValidatorRun with per-assertion results

Validation runs are internal mission-loop operations: Fusion does not create visible 🔍 Validate: board tasks for single-feature validation.

interface MissionValidatorRun {
  id: string;
  featureId: string;
  missionId: string;
  taskId: string;
  triggerType: "manual" | "automatic";
  implementationAttempt: number;
  validatorAttempt: number;
  status: "started" | "passed" | "failed" | "blocked" | "error";
  summary: string;
  results: AssertionResult[];
  blockedReason?: string;
  startedAt: string;
  completedAt?: string;
}

Validation timeout: 10 minutes (VALIDATION_TIMEOUT_MS = 10 * 60 * 1000). If the validator times out, the run is marked error and the feature remains in needs_fix for retry.

Phase 5: Fix-Feature Retries

When validation fails, MissionStore.createGeneratedFixFeature() creates a fix feature with lineage tracking:

interface MissionFixFeatureLineage {
  sourceFeatureId: string;      // Original feature being remediated
  fixFeatureId: string;         // New fix feature
  runId: string;                // Validator run that triggered this fix
  failedAssertionIds: string[]; // Assertions that failed
}

The fix feature is auto-planned (converted to tasks) for immediate execution. Each fix increments implementationAttemptCount.

Default retry budget: 3 (DEFAULT_IMPLEMENTATION_RETRY_BUDGET). When implementationAttemptCount >= maxRetryBudget, the feature transitions to blocked.

Phase 6: Blocked Handoff

A feature transitions to blocked when:

1. All retry budget is exhausted (implementationAttemptCount >= maxRetryBudget)
2. Validation continues to fail
3. Root cause cannot be resolved through iteration

Blocked semantics:

• Autopilot stops advancing the slice containing the blocked feature
• MilestoneValidationRollup.state reflects blocked assertions
• The feature remains in blocked state until operator intervention

On engine restart, recoverActiveMissions() re-enqueues features in validating or needs_fix states from the activeValidations set, ensuring no validation work is lost.

Autopilot / Scheduler Interplay

The scheduler and autopilot collaborate through a carefully ordered call sequence:

1. Task completes → scheduler detects completion
2. scheduler.missionExecutionLoop.processTaskOutcome() — validation FIRST
   - Finds linked feature, runs AI validation, records MissionValidatorRun
3. autopilot.handleTaskCompletion() — feature status sync SECOND
   - Syncs feature status from task state, advances slice if complete
4. scheduler filters blocked missions from further advancement (line ~532)

Autopilot vs Execution Loop retry tracking:

• Autopilot: Per-task retry tracking for slice/feature completion events
• Execution Loop: implementationAttemptCount for retry budget enforcement (default: 3)

These are independent tracking mechanisms — autopilot monitors mission progress while the execution loop manages feature-level retry budgets.

Telemetry and Observability

MissionHealth snapshot fields:

• activeSlices, activeFeatures, blockedFeatures
• validationState, validationRollup
• inProgressCount, passedCount, failedCount, blockedCount

MissionEvent audit types:

• slice_activated, feature_planned, feature_completed
• validation:started, validation:passed, validation:failed, validation:blocked
• fix_feature:created, feature:blocked

Validator run telemetry:

• triggerType — manual vs automatic
• implementationAttempt — which retry attempt this was
• validatorAttempt — how many validator runs for this implementation
• status — started | passed | failed | blocked | error
• summary — natural language summary of results

Assertion failure records:

interface MissionAssertionFailureRecord {
  assertionId: string;
  assertionTitle: string;
  expected: string;
  actual: string;
  message: string;
}

Full state snapshots: MissionFeatureLoopSnapshot captures complete loop state including all validator runs and lineage chains for post-mortem analysis.

Operator Troubleshooting

Symptom	Diagnosis	Resolution
Feature stuck in "validating"	activeValidations set may be stale; engine restart needed	Check logs for validator errors; restart engine to trigger recoverActiveMissions()
Fix feature not auto-planning	planFeature() may have errored; check logs	Manual planning via fn mission plan-feature <id>; investigate planFeature() errors
Budget exhaustion loop	implementationAttemptCount >= maxRetryBudget (default: 3)	Increase maxRetryBudget in mission settings or fix root cause
Blocked mission not advancing	MilestoneValidationRollup.state shows blocked	Identify blocked assertions; operator must resolve root cause
Validation agent errors	AI session creation failed or VALIDATION_TIMEOUT_MS (10 min) exceeded	Check model configuration and logs; verify AI provider auth
No validation runs after task completion	processTaskOutcome() not called; check scheduler logs	Verify mission linkage on feature → task mapping; check scheduler event handlers
Recovery after engine restart	Features in validating/needs_fix state may not re-enqueue	recoverActiveMissions() should run on startup; check recovery log count

Parity Verification Tests

This lifecycle is validated by integration tests in two dependent tasks:

FN-1571 — Core parity tests:

• packages/core/src/mission-factory-parity.integration.test.ts — MissionStore rollups, assertion persistence, validator run records, fix feature lineage
• packages/engine/src/mission-factory-parity.integration.test.ts — Scheduler/autopilot/runtime parity with the validation loop

FN-1572 — Dashboard parity tests:

• packages/dashboard/src/mission-e2e.test.ts — API contract telemetry round-trip (MissionContractAssertion → validator run → MissionHealth)
• packages/dashboard/app/components/__tests__/MissionManager.test.tsx — UI blocked/iterating state rendering

Screenshot

See also: Multi-Project and Task Management.