| name | loop-engineering |
| description | Design and operate loop-engineered agent systems in Claude Code and Cursor. Use for loop engineering, harness design, Ralph loops, /loop, /goal, agent hub, self-improving agents, SKILL.md optimization, or choosing installable loop tooling from the research corpus. |
Loop Engineering
Operational skill distilled from 125-source full ingest (93 non-GitHub line-indexed + 33 GitHub code audits). Load REFERENCE.md for doctrine; INSTALL.md for code-backed installs; CORPUS_INDEX.md for source digests.
v2 requirement — evidence before recommendation
Before recommending any repo or install path:
- Run
python3 scripts/load-digest.py --repo {slug} OR read data/repo-audits/{owner__repo}.md
- Cite evidence IDs (E###) or audit locators (
file:line) in your answer
- Flag README-vs-code mismatches when audit notes them
Do not recommend installs from REFERENCE.md alone.
When to use
- User asks to design a loop, harness, or agent workflow
- Choosing between
/loop, /goal, Routines, Ralph, or custom bash engines
- Picking an installable repo vs custom skill/agent
- Wiring verification, state write-back, or human-in-the-loop gates
Decision tree
Need recurring agent work?
├─ Yes → Stop condition verifiable?
│ ├─ Yes → Maturity path (below)
│ └─ No → Fix stop condition first; do not schedule
└─ No → Single-shot skill dispatch; not a loop
Maturity path (jpoindexter / corpus consensus):
1. Reliable manual run (one skill, one outcome)
2. Encode as SKILL.md
3. Add state file or kernel write-back
4. Wrap in gated loop (mechanical + human gate)
5. Schedule via /loop or /goal
Loop contract template
Every loop design MUST specify:
| Field | Question |
|---|
| Trigger | Schedule, event, or human /loop |
| Input state | What the agent reads (files, DB, kernel) |
| Skill/playbook | Which SKILL.md stages run |
| Verifier | Separate checker sub-agent or mechanical gate |
| Stop condition | Boolean test — not vibes |
| Write-back | What persists after each cycle |
| Human gate | When human must approve before next cycle |
Harness primitives (use first)
| Primitive | Use when |
|---|
/loop | Fixed interval re-run of prompt or slash-command |
/goal | Run until separate model grades "done" |
| Routines | Anthropic-documented recurring workflows |
| Sub-agents | Maker builds; checker verifies (never same agent) |
| Context kernel | Cross-session state at .kernel/KERNEL.md |
See portability kit Automations/README.md for heartbeat layer.
Repo recommendation (code-backed)
Required: load audit before recommending.
python3 ~/.claude/skills/loop-engineering/scripts/load-digest.py --repo cobusgreyling/loop-engineering
python3 ~/.claude/skills/loop-engineering/scripts/load-digest.py --source S02
python3 ~/.claude/skills/loop-engineering/scripts/repo-pick.py --task "loop init"
Default layered stack (v2 code audit confirmed):
- Harness
/loop + /goal (built-in)
cobusgreyling/loop-engineering — 201 files read, score 9.62- Optional harness:
earendil-works/pi (843 files)
- Optional registry:
xpriment626/pi-factory (68 files, SQLite blackboard)
Dispatch rules
- Loop architecture design → dispatch
loop-engineering-architect agent
- Implementation → dispatch domain specialist (never orchestrator)
- Verification →
superpowers:verification-before-completion + code-reviewer
- Skill authoring from loop learnings →
write-a-skill after one reliable manual run
Anti-patterns
- Unattended loops without stop conditions
- Self-grading (same agent verifies its own work)
- Re-prompting full context each cycle instead of skills + state
- Confusing emosamastudio/agent-hub (job scheduler) with Sewell Agent Hub (entity registry)
Refresh
Re-run when corpus grows:
python3 research/loop-engineering-agent-hub-2026/scripts/ingest_corpus_full.py
python3 research/loop-engineering-agent-hub-2026/scripts/audit_github_repos.py
python3 research/loop-engineering-agent-hub-2026/scripts/build_evidence_v2.py
python3 research/loop-engineering-agent-hub-2026/scripts/synthesize_doctrine_v2.py
Copy updated synthesis → REFERENCE.md, INSTALL.md, CORPUS_INDEX.md.
