Restores cognitive state from an atomic checkpoint in .tasks/checkpoints/[task_id].md, enabling instant recovery at the exact point of failure without re-running the full task.
Scanned 5/27/2026
Install via CLI
openskills install tranhieutt/software_development_department---
name: resume-from
type: workflow
description: "Restores cognitive state from an atomic checkpoint in .tasks/checkpoints/[task_id].md, enabling instant recovery at the exact point of failure without re-running the full task."
argument-hint: "<task_id>"
user-invocable: true
allowed-tools: Read, Write, Glob, Bash
effort: 2
when_to_use: "Use after an agent crash, session restart, or context compaction when a specific task was interrupted mid-execution. Requires a checkpoint previously written by /save-state <task_id>."
---
# Resume From Checkpoint
Restore the working context of a specific task from its atomic checkpoint at `.tasks/checkpoints/[task_id].md`, then continue execution from the exact next step — without re-running completed work.
## Steps
### 1. Validate argument
`$ARGUMENTS` must contain a `task_id`. If missing or empty:
```text
❌ Usage: /resume-from <task_id>
Example: /resume-from 042
Example: /resume-from auth-api
Available checkpoints:
[Run: ls .tasks/checkpoints/ and list files excluding .gitkeep]
```
Stop here if no `task_id` is provided.
### 2. Load checkpoint
Read `.tasks/checkpoints/[task_id].md`.
If the file does not exist:
```text
❌ No checkpoint found for task: [task_id]
Expected: .tasks/checkpoints/[task_id].md
Available checkpoints:
[List files in .tasks/checkpoints/ excluding .gitkeep]
Tip: Run /save-state [task_id] first to create a checkpoint.
```
Stop here if file is missing.
### 3. Parse and surface checkpoint
Extract the following fields from the checkpoint and display them clearly:
```text
🔁 Resuming task: [task_id]
Agent: [agent_id]
Saved at: [saved_at]
Retry count: [retry_count]
📄 Output Snapshot (last known state):
[output_snapshot content]
✅ Completed Steps:
[completed steps list]
⏭️ Next Step:
[next_step content]
❓ Open Questions:
[open_questions content — or "None" if empty]
📁 Files Modified So Far:
[files_modified list]
```
### 4. Apply exponential backoff if retrying
Check `retry_count` in the checkpoint frontmatter:
- `retry_count = 0` → proceed immediately, no wait
- `retry_count = 1` → wait 2s before continuing
- `retry_count = 2` → wait 4s before continuing
- `retry_count = 3` → wait 8s before continuing
- `retry_count >= 4` → surface a warning:
```text
⚠️ This task has failed [retry_count] times.
Continuing, but consider escalating to a senior agent or the user
if the same error recurs.
```
Then increment `retry_count` and update `backoff_next_s` (double the previous value, max 64s) in the checkpoint file before proceeding.
### 5. Resume execution
Hand off context to the appropriate agent (`agent_id` from checkpoint) with the following instruction:
> "You are resuming task `[task_id]`. The completed steps and output snapshot above are already done — do NOT repeat them. Your only job is to execute the **Next Step** listed above and continue from there."
### 6. Update checkpoint on success
When the task completes successfully, update `.tasks/checkpoints/[task_id].md`:
- Set `status: completed`
- Set `completed_at: [ISO timestamp]`
- Append to `## Completed Steps`
Print:
```text
✅ Task [task_id] completed successfully.
Checkpoint updated → .tasks/checkpoints/[task_id].md (status: completed)
```
---
## Checkpoint lifecycle
```
/save-state [task_id] → creates .tasks/checkpoints/[task_id].md (status: in_progress)
/resume-from [task_id] → reads checkpoint, increments retry_count, resumes
→ on success: sets status: completed
```
Completed checkpoints are kept for audit — they are never auto-deleted.
To list all checkpoints: `ls .tasks/checkpoints/`
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