ralph-resume

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:

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.

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}...