Skip to content
Development
Skill

/ralph-resume

Resume an interrupted agent loop from last checkpoint

From plugin
aiwg
211200 skills199 agents26 commands
Install
$ npx -y skills add jmagly/aiwg --skill ralph-resume --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/ralph-resume

Context preview

The summary Claude sees to decide when to auto-load this skill.

Resume an interrupted agent loop from last checkpoint

SKILL.md

ralph-resume.SKILL.md
namespace: aiwg
name: ralph-resume
platforms: [all]
description: Resume an interrupted agent loop from last checkpoint
commandHint:
  argumentHint: '[--max-iterations N] [--timeout M --interactive --guidance "text"]'
  allowedTools: "Task, Read, Write, Bash, Glob, Grep, TodoWrite, Edit"
  model: haiku
  category: automation
  orchestration: true
  modelRole: efficiency
  modelTier: economy

<!-- AIWG-SKILL-CALLOUT --> > **Skill access pattern (post-kernel-pivot, 2026.5+)** > > Skill names referenced in this document are AIWG skills, **not slash commands**. Most are not kernel-listed and cannot be invoked as `/skill-name` by the platform. Reach them via: > > ```bash > aiwg discover "<capability>" > aiwg show skill <name> > ``` > > Only kernel-listed skills (`aiwg-doctor`, `aiwg-refresh`, `aiwg-status`, `aiwg-help`, `use`, `steward`) are directly invokable as slash commands. See [skill-discovery rule](../../../addons/aiwg-utils/rules/skill-discovery.md).

Al Resume

Resume a paused or interrupted agent loop.

Usage

/ralph-resume                       # Resume with existing settings
/ralph-resume --max-iterations 20   # Resume with higher iteration limit
/ralph-resume --timeout 120         # Resume with longer timeout

Parameters

--max-iterations N

Override the maximum iterations limit. Useful when loop stopped at limit but was making progress.

--timeout M

Override the timeout in minutes. Useful when loop timed out but task is close to completion.

Your Actions

Step 1: Load State

1. Read `.aiwg/ralph/current-loop.json` 2. Verify loop can be resumed (status != 'success', status != 'aborted') 3. Load iteration history and learnings

**If no resumable loop**:

No agent loop to resume.

Status: {status}

{If success}: Loop completed successfully. Start a new loop with /ralph
{If aborted}: Loop was aborted. Start fresh with /ralph
{If no state}: No loop found. Start with /ralph "task" --completion "criteria"

Step 2: Update Settings

Apply any parameter overrides:

  • Update `maxIterations` if --max-iterations provided
  • Update `timeoutMinutes` if --timeout provided
  • Reset timeout start time for extended timeout

Step 3: Resume Execution

Continue the agent loop pattern:

1. Display resume status:

Resuming Agent Loop

Task: {task}
Completion: {completion}
Previous iterations: {N}
Remaining iterations: {max - N}

Last result: {lastResult}
Learnings so far: {learnings}

Continuing from iteration {N+1}...

2. Execute next iteration with accumulated learnings 3. Follow standard agent loop verification 4. Continue until success or new limits reached

Step 4: Handle Completion

Same as `ralph` - generate completion report on success or limit.

Resume Context

When resuming, include in the task context:

## Agent Loop Resume Context

**Original Task**: {task}
**Completion Criteria**: {completion}

**Previous Iterations**: {N}
**Accumulated Learnings**:
{for each iteration}
- Iteration {i}: {action} -> {result}. Learned: {learnings}
{end for}

**Current State**:
- Last attempt: {lastResult}
- Key insight: {most recent learning}

**Your Goal**:
Continue iterating from iteration {N+1}.
Apply learnings from previous iterations.
Verify against completion criteria after each attempt.

Error Handling

**Loop completed successfully**:

This agent loop already completed successfully.

Final status: SUCCESS
Iterations: {N}
Report: .aiwg/ralph/completion-{timestamp}.md

To run again, start a new loop:
  /ralph "task" --completion "criteria"

**Loop was aborted**:

This agent loop was aborted and cannot be resumed.

To start fresh with the same task:
  /ralph "{original task}" --completion "{original completion}"

**State corrupted**:

Agent loop state is corrupted or incomplete.

Options:
1. Start fresh: /ralph "task" --completion "criteria"
2. Clean up: rm -rf .aiwg/ralph/ then start new loop

Example Scenarios

Max Iterations Override

Previous loop stopped at iteration 10:

/ralph-resume --max-iterations 20

Continues with 10 more iterations available.

Timeout Override

Previous loop timed out at 60 minutes:

/ralph-resume --timeout 120

Continues with fresh 120-minute timeout.

Simple Resume

Loop interrupted (network, restart, etc.):

/ralph-resume

Continues from last checkpoint with original settings.

Related

  • `ralph-status` - Check what state the loop is in
  • `ralph-abort` - Stop instead of resume
  • `ralph` - Start new loop

References

  • @$AIWG_ROOT/agentic/code/addons/ralph/README.md — Ralph addon overview and loop executor documentation
  • @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/vague-discretion.md — Loop termination and iteration limit rules
  • @$AIWG_ROOT/docs/cli-reference.md — CLI reference for ralph-resume and related commands
  • @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/instruction-comprehension.md — Re-reading original task instructions on resume
Read more
Ships withaiwg

Reusable project context and specialist workflows for the AI tools you already use. Plan software, coordinate specialist reviews, prepare campaigns, investigate incidents, organize research, curate media, and maintain operational knowledge.

Get the whole plugin

Other skills on aiwg.