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 (
```
/ideate
```
)
Transitioning between workflow phases
Restoring context after summarization (
```
/rehydrate
```
)
Saving progress for later continuation (
```
/checkpoint
```
)

Phase Transitions

Valid transitions, guards, and prerequisites for all workflow types are documented in

references/phase-transitions.md

. CRITICAL: When a transition has a guard, send the prerequisite

updates

and

phase

in a single

set

call — updates apply before guards evaluate.

Schema Discovery

Use

exarchos_workflow({ action: "describe", actions: ["set", "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

/ideate

, use

mcp__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
```
ideate
```
```
debug
```
→ starts in
```
triage
```
```
refactor
```
→ starts in
```
explore
```
```
oneshot
```
→ starts in
```
plan
```
(skips ideate entirely)

Workflow Types at a Glance

```
feature
```
— full
```
ideate → plan → delegate → review → synthesize
```
for real features with subagent dispatch and two-stage 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__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

Use

mcp__exarchos__exarchos_workflow

with

action: "set"

with

featureId

and either

updates

phase

, or both:

Update phase:
```
phase: "delegate"
```

Set artifact path:

updates: { "artifacts.design": "docs/designs/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" } }

Phase + updates together:

phase: "delegate"

updates: { "artifacts.plan": "docs/plans/plan.md" }

Worktree status values:

'active' | 'merged' | 'removed'

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:

Replace the whole array (use this when the plan is being revised wholesale; matches the issue #1003 contract):

typescript

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

Edit one task by its array index:

typescript

exarchos_workflow({
  action: "set",
  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.

Append a new task by writing to the next-free index. If the array currently has length

, write to

tasks[N]

typescript

// Suppose tasks already contains T-001 and T-002 (length 2). To append:
exarchos_workflow({
  action: "set",
  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__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, the SessionStart hook automatically reconciles on resume. For manual verification, run the reconciliation script:

typescript

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
`/ideate` starts	Create state file
Design saved	Set `artifacts.design` , phase = "plan"
Plan saved	Set `artifacts.plan` , populate tasks, phase = "plan-review"
Plan-review gaps found	Set `planReview.gaps` , auto-loop to plan
Plan-review approved	Set `planReview.approved = true` , phase = "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:

markdown

After saving design:
1. Update state: `.artifacts.design = "<path>"`
2. Update state: `.phase = "plan"`

implementation-planning/SKILL.md:

markdown

After saving plan:
1. Update state: `.artifacts.plan = "<path>"`
2. Populate `.tasks` from plan
3. Update state: `.phase = "delegate"`

delegation/SKILL.md:

markdown

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

Best Practices

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

Troubleshooting

MCP Tool Call Failed

If an Exarchos MCP tool returns an error:

Check the error message — it usually contains specific guidance
Verify the workflow state exists: call
```
mcp__exarchos__exarchos_workflow
```
with
```
action: "get"
```
and the featureId
If "version mismatch": another process updated state — retry the operation

If state is corrupted: call

mcp__exarchos__exarchos_workflow

with

action: "cancel"

and

dryRun: true

State Desync

If workflow state doesn't match git reality:

The SessionStart hook runs reconciliation automatically on resume
If manual check needed: compare state file with
```
git log
```
and branch state

Update state via

mcp__exarchos__exarchos_workflow

with

action: "set"

to match git truth

Checkpoint File Missing

If the PreCompact hook can't find state to checkpoint:

Verify a workflow is active: call
```
mcp__exarchos__exarchos_workflow
```
with
```
action: "get"
```
and the featureId
If no active workflow: the hook will silently skip (expected behavior)
If workflow exists but checkpoint fails: check disk space and permissions

Resume Finds Stale State

If state references branches or worktrees that no longer exist:

The SessionStart hook handles reconciliation automatically
It updates state to reflect current git reality
Missing branches are flagged in the session-start output

Multiple Active Workflows

If multiple workflow state files exist:

The system uses the most recently updated active (non-completed) workflow

Use

mcp__exarchos__exarchos_workflow

with

action: "cancel"

and

dryRun: true

on stale workflows to preview cleanup

Cancel stale workflows before starting new ones

Example Workflow

Start new workflow: Use

mcp__exarchos__exarchos_workflow

with

action: "init"

with

featureId: "user-authentication"

workflowType: "feature"

After design phase: Use

mcp__exarchos__exarchos_workflow

with

action: "set"

with:

```
featureId: "user-authentication"
```
```
phase: "plan"
```

updates: { "artifacts.design": "docs/designs/2026-01-05-user-auth.md" }

Check state: Use

mcp__exarchos__exarchos_workflow

with

action: "get"

with

featureId: "user-authentication"

Resume after context loss: Use

mcp__exarchos__exarchos_workflow

with

action: "get"

with

featureId: "user-authentication"

to get context restoration output

workflow-state

NPX Install

Tags

SKILL.md Content

Workflow State Management Skill

Overview

Triggers

Phase Transitions

Schema Discovery

State Location

State Operations

Initialize State

Workflow Types at a Glance

Read State

Update State

Editing the
`tasks`
array

Get Summary

Reconcile State

Integration Points

When to Update State

Oneshot-specific state updates

Automatic State Updates

State Schema

Best Practices

Troubleshooting

MCP Tool Call Failed

State Desync

Checkpoint File Missing

Resume Finds Stale State

Multiple Active Workflows

Example Workflow