agentic/code/addons/agent-loop/skills/ralph-resume/SKILL.md
Resume an interrupted agent loop from last checkpoint
npx skillsauth add jmagly/aiwg ralph-resumeInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
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-nameby 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.
Resume a paused or interrupted agent loop.
/ralph-resume # Resume with existing settings
/ralph-resume --max-iterations 20 # Resume with higher iteration limit
/ralph-resume --timeout 120 # Resume with longer timeout
Override the maximum iterations limit. Useful when loop stopped at limit but was making progress.
Override the timeout in minutes. Useful when loop timed out but task is close to completion.
.aiwg/ralph/current-loop.jsonIf 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"
Apply any parameter overrides:
maxIterations if --max-iterations providedtimeoutMinutes if --timeout providedContinue the agent loop pattern:
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}...
Same as ralph - generate completion report on success or limit.
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.
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
Previous loop stopped at iteration 10:
/ralph-resume --max-iterations 20
Continues with 10 more iterations available.
Previous loop timed out at 60 minutes:
/ralph-resume --timeout 120
Continues with fresh 120-minute timeout.
Loop interrupted (network, restart, etc.):
/ralph-resume
Continues from last checkpoint with original settings.
ralph-status - Check what state the loop is inralph-abort - Stop instead of resumeralph - Start new loopdata-ai
Report which research-corpus radar sidecars are overdue for refresh. Computes staleness (days since last refresh vs the cadence window) for every radar, sorted most-overdue-first. Runs via `aiwg corpus radar-status`.
data-ai
Aggregate research-corpus radar sidecars into a corpus or per-cluster freshness report — totals, overdue count, per-cluster / per-GRADE / per-trajectory breakdowns, an overdue table, and per-radar rationale snippets. Runs via `aiwg corpus radar-report`.
testing
Scaffold radar/freshness sidecars for research-corpus REFs. Pulls title/authors from the citation sidecar and GRADE from the analysis doc, defaults the refresh cadence from GRADE and the cluster from a corpus-local map, and stamps documentation/radar/REF-XXX-radar.md. Runs via `aiwg corpus radar-init`.
data-ai
Compute an entity's publication trajectory — per-year paper counts, topic drift, hot-streak detection (≥3 consecutive A-grade years), and career phase. Runs via `aiwg corpus profile-temporal`.