Install
$ agentstack add skill-qwwiwi-agentos-skills-public-loop-coding ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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% · Ship
Escalation
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.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: qwwiwi
- Source: qwwiwi/agentos-skills-public
- License: MIT
Install and usage instructions live in the source repository linked above.
Reviews
No reviews yet, be the first.
Write a review
Versions
- v0.1.0 Imported from the upstream source.