loop-coding
Skill4 starsChanged 4 months agoMITView on GitHub
Orchestrates implementation-heavy coding work — migrations, major refactors, rewrites, multi-file feature builds, auth/API overhauls, system rebuilds — via a 7-phase pipeline (research, audit, plan, implement, review, fix-loop, ship). Scripts-first (70%+ automated), dual-model critique (Opus + Codex), auto-generated helper sub-skills via skill-creator, staging-first deploy. Trigger on: migrate, rewrite, rebuild, overhaul, large feature — including Russian миграция, крупный рефакторинг, переписать, переделать систему, большая фича, лупкодинг. Do NOT use for: single-file edits, fixes under 5 lines, dependency bumps, typo or link fixes, docs-only changes, adding a log line or type hint, code review of existing PRs, ADR or planning-only requests, content writing or naming tasks (use gsd-plan-phase or brainstorming for planning).
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1 other project uses a version of this.
Adopted by
Most recently taken up by
- 0xArx/loopcoding-skilltheir own version, first seen Jun 9, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- 0xArx/loopcoding-skill★ 2same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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The file
Show its rules and text
We split this skill into the rules it gives an agent
13 rules. About 0 are common, 8 are distinctive, and 5 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈8
Distinctive · estimate
This author's own choices. Worth a look.
5
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 16
Respect existing code: Before building new, audit what already exists: our repos (your-repos), code in ~/.claude/, instructions in …
- Distinctive: line 22
Max 3 fix iterations: If review-fix loop does not converge in 3 iterations, escalate to prince with remaining issues.
- Very specific: line 24
Staging-first deploy: If project has deploy.sh: staging is autonomous, production requires prince explicit "да, на prod".
- Distinctive: line 30
Do NOT trigger on: single bug fixes, typo corrections, 1-file edits, planning-only discussions, documentation updates.
- Distinctive: line 52
Every invocation creates a dedicated directory:
- Very specific: line 85
Test strategy per language -> references/test-strategy.md
- Distinctive: line 90
Every formalizable step has a script.
- Very specific: line 131
After every phase transition, render and send the bar to prince.
- Distinctive: line 147
After 3 fix-loop iterations with remaining critical/high issues -> Telegram to prince with REVIEW.md + FIX-LOG.md attached.
- Distinctive: line 148
Before production deploy (always) -> explicit prince approval required.
- Distinctive: line 149
If research finds no viable approach and no patterns exist -> ask prince for direction.
- Distinctive: line 150
If a rented skill fails security scan AND no alternative exists -> report to prince, do not use skill.
- Very specific: line 152
Use scripts/escalate.sh - it sends the right files with the right caption.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
loop-coding
Orchestrator for large coding tasks. I (Silvana/Opus) coordinate; subagents and scripts do the heavy lifting.
Core principles
- Scripts-first. If a step can be formalized as a shell/python script, it MUST be a script, not an AI call. Scripts are cheaper, faster, deterministic, and free from token drift. AI is reserved for: generating prompts for subagents, reading merged artifacts, making judgment calls, writing actual code, critiquing code.
- Codex for critique, Opus for code, double only on Review. Research is dual (Sonar+Sonnet, parallel). Audit and Plan are Codex GPT-5.5 ONLY — Opus is NOT spawned for these phases (Codex is the stronger critic + architect, and Opus subscription is the scarce resource we protect). Implement is Opus (best in our stack). Review is the only dual-model phase: Codex + Opus in parallel, scripts merge outputs and flag divergence as risk. Rationale: Audit/Plan = single critic is enough when the critic is GPT-5.5; Review = code already exists, two pairs of eyes catch different bugs, worth the Opus token.
- Respect existing code. Before building new, audit what already exists: our repos (your-repos), code in
~/.claude/, instructions in CLAUDE.md / rules.md / SOUL.md. Do NOT reinvent if a solution already exists. - Auto-generate helper skills when needed. After audit, if a gap is detected that would repeat 3+ times and has no existing solution, invoke the global
skill-creatorat~/.claude/skills/skill-creator/via an Opus subagent with a pre-answered non-interactive brief (otherwise skill-creator's interview phase stalls). Validate every generated sub-skill withquick_validate.pybefore use.run_eval.pyfor trigger evaluation works on Max OAuth;run_loop.pydescription optimization requiresANTHROPIC_API_KEYand is blocked in this workspace. Full workflow + path conventions:references/sub-skill-generation.md. - Rent external skills safely. Skills from skills.sh can be downloaded into
rented-skills/{task-id}/for the duration of the task, but ONLY after passing security scan (scripts/skill-security-scan.sh). - Max 3 fix iterations. If review-fix loop does not converge in 3 iterations, escalate to prince with remaining issues.
- Staging-first deploy. If project has deploy.sh: staging is autonomous, production requires prince explicit "да, на prod". Push to git is autonomous.
When to use
Trigger on: миграция, переезд, крупный рефакторинг, большая фича, переделать систему, loop-coding, лупкодинг, полная переработка.
Do NOT trigger on: single bug fixes, typo corrections, 1-file edits, planning-only discussions, documentation updates.
Sibling skill — fast-loop-coding (~/.claude/skills/fast-loop-coding/SKILL.md): for tasks 50-300 LOC, 1-3 files, single subsystem, 15-30 min. 4 phases instead of 7, no parallel research, no double review, 1 fix iteration. Use it when task fits its decision tree; escape to this skill mid-task if scope grows past 300 LOC / 3 files / multi-subsystem.
Workflow
Seven phases, strict order:
1. Research (Sonar + Sonnet + GitHub-scout + skill-scout, parallel)
2. Audit (Codex GPT-5.5 ONLY; respect existing code)
3. Plan (Codex GPT-5.5 ONLY — arch + impl + test skeletons brief)
4. Implement (Opus coder subagents; run tests after each commit)
5. Review (Codex + Opus parallel; extend tests) ← only dual-model phase
6. Fix-loop (max 3 iterations; else escalate)
7. Ship (git push auto; staging auto; prod requires prince OK)Each phase produces an artifact in the run directory and updates the milestone bar.
Run directory
Every invocation creates a dedicated directory:
~/.claude/loop-coding-runs/{YYYY-MM-DD}-{task-slug}/
├── RESEARCH.md (phase 1 output)
├── AUDIT.md (phase 2 output)
├── PLAN.md (phase 3 output)
├── REVIEW.md (phase 5/6 output; severity-sorted)
├── FIX-LOG.md (iteration log)
├── DEPLOY.md (phase 7 log)
├── tests/ (TDD skeletons from Plan phase)
└── rented-skills/ (external skills used during this task)Artifacts persist after task completion for audit trail. Archived to runs/archive/ by a monthly cron.
Phase execution
For each phase, read the corresponding reference file for detailed instructions:
- Phase 1 Research ->
references/phase-1-research.md - Phase 2 Audit ->
references/phase-2-audit.md - Phase 3 Plan ->
references/phase-3-plan.md - Phase 4 Implement ->
references/phase-4-implement.md - Phase 5 Review ->
references/phase-5-review.md - Phase 6 Fix-loop ->
references/phase-6-fix-loop.md - Phase 7 Ship ->
references/phase-7-ship.md
Cross-cutting concerns:
- GitHub scouting ->
references/github-scout.md(min 2000 stars, prefer 10k+) - skills.sh scouting + rent flow ->
references/skill-scout.md - Security scan for external skills ->
references/skill-security.md - Test strategy per language ->
references/test-strategy.md - Auto-generation of sub-skills ->
references/sub-skill-generation.md
Scripts (automation backbone)
Every formalizable step has a script. Invoke them, do not reimplement:
| Script | Purpose | Phase |
scripts/init-run.sh {slug} | Create run directory, seed templates | pre-1 |
scripts/github-search.sh {query} | gh search repos stars:>=2000, returns JSON | 1 |
scripts/skill-scout.sh {query} | Search skills.sh catalog, filter by security | 1 |
scripts/skill-security-scan.sh {path} | Static grep + Codex review, verdict safe/risky/reject | 1 |
scripts/rent-skill.sh {url} {run-dir} | Download into rented-skills/, log manifest | 1 |
scripts/return-skill.sh {run-dir} | Clean rented-skills, keep manifest | 7 |
scripts/parallel-review.sh {target} | Spawn Codex + Opus reviewers, merge to REVIEW.md | 2,5 |
scripts/merge-reviews.sh {a} {b} | Two reviews -> consensus + divergence | 2,5 |
scripts/loop-controller.sh {run-dir} | Iteration counter, auto-escalate at 3 | 6 |
scripts/milestone-render.sh {phase} | Render progress bar, send to Telegram | all |
scripts/test-runner.sh {lang|auto} | pytest (py) / pnpm|bun|npm test (ts) / bats (sh) | 4,5 |
scripts/commit-atomic.sh {message} | git add + commit + optional push | 4,7 |
scripts/deploy-helper.sh {env} | Wrapper over project deploy.sh, logs to DEPLOY.md | 7 |
scripts/escalate.sh {run-dir} | Telegram sendDocument to prince after 3 fails | 6 |
Scripts are self-documenting (pass -h for usage).
Model allocation
| Role | Model | Phases |
| Orchestrator | Opus 4.6 (me) | all |
| Research-Sonar | Perplexity sonar-pro | 1 |
| Research-Code | Sonnet 4.6 subagent | 1 |
| Research-GitHub | Sonnet 4.6 + gh CLI | 1 |
| Skill-scout | Sonnet 4.6 subagent | 1 |
| Auditor | Codex GPT-5.5 | 2 |
| Architect + planner | Codex GPT-5.5 | 3 |
| Test-skeleton writer | Opus subagent | 3 (only after Codex plan lands) |
| Coder | Opus subagent(s), up to 5 | 4, 6 |
| Reviewer A | Codex GPT-5.5 | 5 |
| Reviewer B | Opus subagent | 5 |
Codex is never used for research (too slow, too expensive) or for code writing (Opus is stronger in our stack). Codex is strictly critic/architect, and is now the SOLE model for Audit and Plan to offload Opus subscription. Opus only enters during Implement, test-skeleton writing under Codex plan, fix-loop, and Review.
Milestone display
After every phase transition, render and send the bar to prince. Seven segments, one per phase. See scripts/milestone-render.sh.
▰▱▱▱▱▱▱ 14% · Research
▰▰▱▱▱▱▱ 28% · Audit
▰▰▰▱▱▱▱ 42% · Plan
▰▰▰▰▱▱▱ 57% · Implement
▰▰▰▰▰▱▱ 71% · Review
▰▰▰▰▰▰▱ 85% · Fix-loop
▰▰▰▰▰▰▰ 100% · ShipEscalation
Hard stops where the loop cannot proceed autonomously:
- After 3 fix-loop iterations with remaining critical/high issues -> Telegram to prince with REVIEW.md + FIX-LOG.md attached.
- Before production deploy (always) -> explicit prince approval required.
- If research finds no viable approach and no patterns exist -> ask prince for direction.
- If a rented skill fails security scan AND no alternative exists -> report to prince, do not use skill.
Use scripts/escalate.sh - it sends the right files with the right caption.
Starting a run
RUN_DIR=$(bash scripts/init-run.sh "cognee-migration")
bash scripts/phase-1-research.sh "$RUN_DIR" "migrate to Cognee graph RAG"
bash scripts/parallel-review.sh audit "$RUN_DIR"Orchestration is primarily shell-driven; I step in for judgment calls between phases and to spawn subagents for code-writing tasks.
Versioning
Current: v1.0 (2026-04-17).
Skill evolves via iteration after real use. Feedback from each run goes into ~/.claude/skills/LEARNINGS.md and promotes into this SKILL.md when score >= 0.8.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

