lvlup-sw/workflow-state

Workflow State Management Skill

Overview

Manage persistent workflow state that survives context auto-summarization.

State files store: task details, worktree locations, PR URLs, and review status.

Triggers

Activate this skill when:

• Starting a new workflow (/exarchos:ideate)
• Transitioning between workflow phases
• Restoring context after summarization (/exarchos:rehydrate <featureId>)
• Saving progress for later continuation (/exarchos:checkpoint)

Phase Transitions

Valid transitions, guards, and prerequisites for all workflow types are documented in references/phase-transitions.md. CRITICAL: Phase mutation is a separate action from field mutation. When a transition has a guard, action: "update" the prerequisite fields first, then action: "transition" — guards read the most recent state, so updates land before guards evaluate. Attempting to mutate phase via action: "update" returns a RESERVED_FIELD error pointing at transition (see "Reserved fields" below).

Schema Discovery

Use exarchos_workflow({ action: "describe", actions: ["update", "init", "get"] }) for parameter schemas and exarchos_workflow({ action: "describe", playbook: "feature" }) for phase transitions, guards, and playbook guidance. For the lightweight oneshot variant (with its implementing → synthesize|completed choice state driven by synthesisPolicy), call exarchos_workflow({ action: "describe", playbook: "oneshot" }) — oneshot is a first-class playbook alongside feature/debug/refactor. Use exarchos_event({ action: "describe", eventTypes: ["workflow.transition", "task.completed"] }) for event data schemas.

State Location

Workflow state lives in the MCP event store, not the filesystem. Use exarchos_workflow get to read state and exarchos_view pipeline to discover active workflows. Do not scan ~/.claude/workflow-state/*.state.json — that path is legacy and may be stale or empty.

State Operations

For full MCP tool signatures, error handling, and anti-patterns, see references/mcp-tool-reference.md.

Initialize State

At the start of /exarchos:ideate, use mcp__plugin_exarchos_exarchos__exarchos_workflow with action: "init" with:

• featureId: the workflow identifier (e.g., "user-authentication")
• workflowType: one of "feature", "debug", "refactor", "oneshot"
• synthesisPolicy (optional, oneshot only): one of "always", "never", "on-request" (default "on-request") — silently ignored for non-oneshot types

This creates a new workflow state entry. The initial phase depends on workflowType:

• feature → starts in plan
• debug → starts in triage
• refactor → starts in explore
• oneshot → starts in plan

Workflow Types at a Glance

• feature — full plan → plan-review → delegate → review → synthesize for real features with subagent dispatch and review
• debug — triage → investigate → (thorough | hotfix) for bug workflows with track selection
• refactor — explore → brief → (polish | overhaul) for code improvements, polish for small and overhaul for multi-task
• oneshot — plan → implementing → (completed | synthesize) for trivial changes; direct-commit by default with an opt-in PR path resolved via a choice-state guard driven by synthesisPolicy and the synthesize.requested event

See @skills/oneshot-workflow/SKILL.md for the lightweight variant's full prose, including the choice-state mechanics and finalize_oneshot trigger.

Read State

Use mcp__plugin_exarchos_exarchos__exarchos_workflow with action: "get" and featureId:

• Full state: Call with just featureId
• Specific field: Add query for dot-path lookup (e.g., query: "phase", query: "tasks")
• Multiple fields: Add fields array for projection (e.g., fields: ["phase", "featureId", "tasks"])

Field projection via fields returns only the requested top-level keys, reducing token cost.

Update State (fields only)

Use mcp__plugin_exarchos_exarchos__exarchos_workflow with action: "update" with featureId and updates. This action mutates non-phase fields only — phase, workflowType, featureId, createdAt, and version are reserved (see "Reserved fields" below).

• Set artifact path: updates: { "artifacts.spec": "docs/specs/2026-01-05-feature.md" }
• Mark task complete (by index): updates: { "tasks[0].status": "complete", "tasks[0].completedAt": "<timestamp>" }
• Add worktree: updates: { "worktrees.wt-001": { "branch": "feature/001-types", "taskId": "001", "status": "active" } }

Worktree status values: 'active' | 'merged' | 'removed'

Transition Phase

Use mcp__plugin_exarchos_exarchos__exarchos_workflow with action: "transition" with featureId and target:

• Advance phase: target: "delegate"

Transitions are HSM-validated and emit a workflow.transition event. Guarded transitions read state after the most recent update, so any updates: {...} that the guard depends on must land first.

Editing the tasks array

The dot-path parser used by set updates recognizes only numeric array brackets (tasks[0], tasks[1], …). Keyed forms like tasks[id=T-001] are NOT supported and now throw an INVALID_INPUT error with a clear message — earlier versions silently wrote to a bogus top-level key, returning success: true while the actual task was untouched. Three patterns are supported:

1. Replace the whole array (use this when the plan is being revised wholesale):

   exarchos_workflow({
     action: "update",
     featureId: "<id>",
     updates: { tasks: [
       { id: "T-001", title: "...", status: "pending" },
       { id: "T-002", title: "...", status: "pending" },
     ]},
   })
   

2. Edit one task by its array index:

   exarchos_workflow({
     action: "update",
     featureId: "<id>",
     updates: { "tasks[0].status": "complete", "tasks[0].completedAt": "<ts>" },
   })
   

   First read tasks (action: "get", query: "tasks") to find the index of the task you want to edit, then set by that index.

3. Append a new task by writing to the next-free index. If the array currently has length N, write to tasks[N]:

   // Suppose tasks already contains T-001 and T-002 (length 2). To append:
   exarchos_workflow({
     action: "update",
     featureId: "<id>",
     updates: { "tasks[2]": { id: "T-003", title: "Follow-up", status: "pending" } },
   })
   

   The parser allows writing one slot past the current length (MAX_ARRAY_GAP = 1); writing further out (tasks[5] against a length-2 array) throws INVALID_INPUT. Read the current tasks length before appending.

Get Summary

For context restoration after summarization, use mcp__plugin_exarchos_exarchos__exarchos_workflow with action: "get" and featureId. This outputs a minimal summary suitable for rebuilding orchestrator context.

Reconcile State

To verify state matches git reality, run /exarchos:rehydrate <featureId> — the rehydration projection folds events newer than the last snapshot and surfaces drift in the returned envelope. For deeper manual verification, run the reconciliation script:

exarchos_orchestrate({
  action: "reconcile_state",
  stateFile: "<state-file>",
  repoRoot: "<repo-root>"
})

On passed: true: State is consistent. On passed: false: Discrepancies found — review output and resolve.

Integration Points

When to Update State

| Event | State Update | |-------|--------------| | /exarchos:ideate starts | init the workflow (initial phase plan) | | Design & Rationale authored | update: { "artifacts.spec": "<path>" } (no transition — plan is the initial phase) | | Decomposition added | update: { "artifacts.plan": "<path>", "tasks": [...] }, then transition target: "plan-review" | | Plan-review gaps found | update: { "planReview.gaps": [...] }, auto-loop to plan | | Plan-review approved | update: { "planReview.approved": true }, then transition target: "delegate" | | Task dispatched | Set task status = "in_progress", startedAt | | Task complete | Set task status = "complete", completedAt | | Worktree created | Add to worktrees object | | Review complete | Update reviews object | | PR created | Set artifacts.pr, synthesis.prUrl | | PR feedback | Append to synthesis.prFeedback |

Oneshot-specific state updates

Oneshot is a first-class workflow type with a compressed lifecycle and an opt-in PR path. The rows below mirror the feature-workflow table above.

| Phase | State updates | Events emitted | |-------|---------------|----------------| | plan (oneshot) | oneshot.planSummary, artifacts.plan, optional oneshot.synthesisPolicy | workflow.transition | | implementing (oneshot) | tasks[].status, artifacts.tests | task.*, optional synthesize.requested (via request_synthesize) | | synthesize (oneshot) | synthesis.prUrl, artifacts.pr | workflow.transition, stack.submitted | | completed (oneshot) | — | workflow.transition (to completed) |

The implementing → synthesize | completed fork is a choice state resolved by finalize_oneshot, which reads the synthesisOptedIn guard (synthesisPolicy + synthesize.requested events). See @skills/oneshot-workflow/SKILL.md for the full opt-in mechanics.

Automatic State Updates

Skills should update state at key moments:

brainstorming/SKILL.md:

After authoring the Design & Rationale section of the unified docs/specs/ artifact:
- `action: "update"` — `updates: { "artifacts.spec": "<path>" }`
  (no transition — `plan` is the initial phase; continue to decomposition in the same phase)

implementation-planning/SKILL.md:

After saving plan:
1. `action: "update"` — `updates: { "artifacts.plan": "<path>", "tasks": [...] }`
2. `action: "transition"` — `target: "plan-review"`

delegation/SKILL.md:

On task dispatch:
- Update task status to "in_progress"
- Add worktree to state if created

On task complete:
- Update task status to "complete"
- Check if all tasks done, suggest checkpoint

State Schema

See docs/schemas/workflow-state.schema.json for full schema.

Key sections:

• version: Schema version (currently "1.1")
• featureId: Unique workflow identifier
• workflowType: Required. One of "feature", "debug", "refactor", or "oneshot"
• phase: Current workflow phase
• artifacts: Paths to design, plan, PR
• tasks: Task list with status
• worktrees: Active git worktrees
• planReview: Plan-review delta analysis results (gaps, approved)
• reviews: Review results
• synthesis: Merge/PR state

Reserved fields

mcp__plugin_exarchos_exarchos__exarchos_workflow with action: "update" rejects two classes of paths with RESERVED_FIELD:

1. Top-level immutable keys — phase, workflowType, featureId, createdAt, version. Set once at init; never mutated directly.
2. Underscore-prefixed paths — any dot-path whose top-level key, or any segment, begins with _ (e.g. _version, _checkpoint.summary, _eventHints). These are projection or event-store metadata.

Alternate write paths:

• phase → mcp__plugin_exarchos_exarchos__exarchos_workflow with action: "transition" and target: "<phase>". Transitions are HSM-validated and emit transition events.
• Underscore-prefixed paths → emit a typed event via mcp__plugin_exarchos_exarchos__exarchos_event with action: "append" (e.g. checkpoint, state.patched). The projection folds the event into the field on the next read.
• workflowType, featureId, createdAt, version → not migratable. If you need a different workflow type, init a new workflow.

A RESERVED_FIELD error envelope now carries a typed data block:

{
  "success": false,
  "error": {
    "code": "RESERVED_FIELD",
    "message": "Cannot update reserved field: phase",
    "data": {
      "rejectedPath": "phase",
      "rule": "`phase` is top-level immutable — set once at init, never directly mutated thereafter.",
      "alternateWritePath": "Use `mcp__plugin_exarchos_exarchos__exarchos_workflow` with `action: \"transition\"` and `target: \"<phase>\"` — phase changes are HSM-validated and emit transition events."
    }
  }
}

Read the full descriptor — including the regex catch-all for underscore paths — via mcp__plugin_exarchos_exarchos__exarchos_workflow with action: "describe" and actions: ["update"]. The returned reservedFields block is the single source of truth.

Best Practices

1. Update often - State should reflect reality at all times
2. Use MCP tools - Prefer workflow-state MCP tools over manual JSON editing
3. Reconcile on resume - Always verify state matches git state
4. Checkpoint at boundaries - Save state before likely context exhaustion
5. Read state, don't remember - After summarization, read from state file

Troubleshooting

MCP Tool Call Failed

If an Exarchos MCP tool returns an error:

1. Check the error message — it usually contains specific guidance
2. Verify the workflow state exists: call mcp__plugin_exarchos_exarchos__exarchos_workflow with action: "get" and the featureId
3. If "version mismatch": another process updated state — retry the operation
4. If state is corrupted: call mcp__plugin_exarchos_exarchos__exarchos_workflow with action: "cancel" and dryRun: true

State Desync

If workflow state doesn't match git reality:

1. Run /exarchos:rehydrate <featureId> — the rehydration projection folds in events newer than the last snapshot
2. If manual check still needed: compare the rehydration document's workflowState / artifacts with git log and branch state
3. Update state via mcp__plugin_exarchos_exarchos__exarchos_workflow with action: "update" to match git truth

Checkpoint Missing

If /exarchos:checkpoint is invoked with no active workflow:

1. Discovery first: call mcp__plugin_exarchos_exarchos__exarchos_workflow with action: "list" to enumerate active workflows; if the list is empty the checkpoint command's "no active workflow" report is correct — exit cleanly
2. If list returns a candidate, verify it: call mcp__plugin_exarchos_exarchos__exarchos_workflow with action: "get" and that featureId
3. If a workflow exists but checkpoint fails: check disk space and permissions on the event store

Resume Finds Stale State

If state references branches or worktrees that no longer exist:

1. Run /exarchos:rehydrate <featureId> — the rehydration document surfaces stale references
2. Compare against git branch -a / git worktree list to identify drift
3. Update via exarchos_workflow update to match git truth

Multiple Active Workflows

If multiple workflow state files exist:

1. The system uses the most recently updated active (non-completed) workflow
2. Use mcp__plugin_exarchos_exarchos__exarchos_workflow with action: "cancel" and dryRun: true on stale workflows to preview cleanup
3. Cancel stale workflows before starting new ones

Example Workflow

1. Start new workflow: Use mcp__plugin_exarchos_exarchos__exarchos_workflow with action: "init" with featureId: "user-authentication", workflowType: "feature"

2. After authoring the Design & Rationale section (plan is already the initial phase — no transition):

   • action: "update", featureId: "user-authentication", updates: { "artifacts.spec": "docs/specs/2026-01-05-user-auth.md" }

3. Check state: Use mcp__plugin_exarchos_exarchos__exarchos_workflow with action: "get" with featureId: "user-authentication"

4. Resume after context loss: Use mcp__plugin_exarchos_exarchos__exarchos_workflow with action: "get" with featureId: "user-authentication" to get context restoration output