Resume Session
Cold-start pickup for a new Claude Code session. Checks sim, seed, pipeline, and gets everything running. Use at the start of every new session.
Score breakdown
Estimated from the available content and source signals.
Model compatibility
Inferred fit is not the same as a recorded hands-on test.
Overview
You are the session resumption agent. When a user starts a new Claude Code session on Rappterbook, run this to pick up where they left off. No context from previous sessions — you reconstruct everything from disk.
Step 1: Read Memory
cat /Users/kodyw/.claude/projects/-Users-kodyw-Projects-rappterbook/memory/MEMORY.md
cat /Users/kodyw/.claude/projects/-Users-kodyw-Projects-rappterbook/memory/project_full_state_2026_03_16.md
This gives you the full context: active seed, repos shipped, pipeline architecture, known issues.
Step 2: Check Sim
ps -p $(cat /tmp/rappterbook-sim.pid 2>/dev/null) > /dev/null 2>&1 && echo "SIM: ALIVE" || echo "SIM: DEAD"
tail -5 logs/sim.log 2>/dev/null
If dead, restart:
nohup bash scripts/copilot-infinite.sh --hours 10 --streams 5 > logs/sim.log 2>&1 &
echo "Sim restarted"
Step 3: Check Active Seed
python3 -c "
import json
s = json.load(open('state/seeds.json'))
a = s.get('active', {})
print(f'Seed: {a.get(\"id\", \"none\")}')
print(f'Text: {a.get(\"text\", \"\")[:80]}')
print(f'Frames: {a.get(\"frames_active\", 0)}')
print(f'Conv: {a.get(\"convergence\", {}).get(\"score\", 0)}%')
print(f'Resolved: {a.get(\"convergence\", {}).get(\"resolved\", False)}')
print(f'Queue: {len(s.get(\"queue\", []))} items')
"
Step 4: Check Code on Disk
For the active project, check if agents have written code:
# Find the active project
for p in projects/*/project.json; do
slug=$(dirname "$p" | xargs basename)
files=$(find "projects/$slug/src" "projects/$slug/docs" -type f -not -name ".gitkeep" -not -path "*__pycache__*" 2>/dev/null | wc -l | tr -d ' ')
if [ "$files" -gt 0 ]; then
echo "$slug: $files files on disk"
find "projects/$slug/src" "projects/$slug/docs" -type f -not -name ".gitkeep" -not -path "*__pycache__*" 2>/dev/null | head -10
fi
done
Step 5: Harvest if Needed
If code exists on disk but hasn't been pushed to the target repo:
python3 scripts/harvest_artifact.py --project {slug} --dry-run
If artifacts found, harvest for real:
python3 scripts/harvest_artifact.py --project {slug} --phase "session-resume"
Step 6: Rebuild Public Dashboards
python3 scripts/build_seed_tracker.py 2>/dev/null
python3 scripts/build_harness_dashboard.py 2>/dev/null
Step 7: Spin Up Temporal Harness
Set up the recurring monitoring crons:
I'll set up the temporal harness:
- Fleet health check every 30 min
- Artifact overseer every 10 min
- Deep analytics every 4 hours
Use CronCreate for each.
Step 8: Report to User
Print a concise status:
SESSION RESUMED
===============
Sim: [ALIVE/DEAD]
Seed: [id] — [text[:60]]
Frames: [N], Convergence: [N]%
Code on disk: [N] files in [project]
Target repo: [url]
Live site: [pages url]
TEMPORAL HARNESS: [running/setting up]
What would you like to do?
Rules
- Always read memory files FIRST — they contain the accumulated context
- If the sim is dead, restart it immediately without asking
- If code is on disk and not harvested, harvest it
- If dashboards are stale, rebuild them
- Set up the temporal harness crons every session (they're session-only)
- Be concise — the user knows the system, they just need current status
Best for
- Use Resume Session when this documented workflow matches the task.
Tips and best practices
- Review the source instructions and adapt inputs before running the workflow.
What This Skill Can Do
AI-generated examples showing real capabilities
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