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Kontinuierlicher Agenten-Loop

Muster für kontinuierliche, autonome Agenten-Loops mit Qualitätstoren, Evaluierungen und Wiederherstellungsmechanismen. Verwende dies, wenn ein Agenten-Loop ausgeführt wird, der sich selbst überprüfen, anhand von Evaluierungen entscheiden und Fehler beheben können muss.

Was ist Kontinuierlicher Agenten-Loop?

Der `continuous-agent-loop` Skill beschreibt ein kanonisches Loop-Muster für KI-Agenten (ab Version 1.8), das das ältere `autonomous-loops` Konzept ablöst. Er definiert eine strukturierte Entscheidungslogik zur Auswahl des richtigen Loop-Typs: Für strikte CI/PR-Steuerung wird `continuous-pr` empfohlen, für RFC-Zerlegung `rfc-dag`, für explorative parallele Generierung `infinite`, andernfalls der Standard `sequential`. Als empfohlener Produktionsstack werden vier kombinierte Muster genannt: RFC-Zerlegung (`ralphinho-rfc-pipeline`), Qualitätstore (`plankton-code-quality` + `/quality-gate`), Evaluierungs-Loop (`eval-harness`) und Sitzungspersistenz (`nanoclaw-repl`). Der Skill behandelt zentrale Fehlermodi wie Loop-Churn ohne messbaren Fortschritt, wiederholte Wiederholungen mit derselben Ursache, Merge-Queue-Staus und Kostenabweichungen durch unbegrenzte Eskalation. Für die Wiederherstellung werden klare Schritte vorgegeben: Loop einfrieren, `/harness-audit` ausführen, Scope auf die fehlerhafte Einheit reduzieren und mit expliziten Akzeptanzkriterien neu starten. Der Skill ist plattformunabhängig für KI-Agenten wie Claude Code, Cursor oder Codex konzipiert.

Funktioniert mit~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/continuous-agent-loop
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Dokumentation

Was macht Kontinuierlicher Agenten-Loop?

Dies ist der kanonische Loop-Skill ab Version 1.8+. Er ersetzt autonomous-loops und behält für eine Version die Kompatibilität bei.

Loop-Auswahl-Fluss

Start
  |
  +-- Strikte CI/PR-Steuerung nötig? -- ja --> continuous-pr
  |
  +-- RFC-Zerlegung nötig? -- ja --> rfc-dag
  |
  +-- Explorative parallele Generierung nötig? -- ja --> infinite
  |
  +-- Standard --> sequential

Kombiniertes Muster

Empfohlener Produktionsstack:

  1. RFC-Zerlegung (ralphinho-rfc-pipeline)
  2. Qualitätstore (plankton-code-quality + /quality-gate)
  3. Evaluierungs-Loop (eval-harness)
  4. Sitzungspersistenz (nanoclaw-repl)

Fehlermodi

  • Loop-Churn ohne messbaren Fortschritt
  • Wiederholte Wiederholungen mit derselben Ursache
  • Merge-Queue-Staus
  • Kostenabweichung durch unbegrenzte Eskalation

Wiederherstellung

  • Loop einfrieren
  • /harness-audit ausführen
  • Scope auf die fehlerhafte Einheit reduzieren
  • Mit expliziten Akzeptanzkriterien neu starten

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

Verwandte Skills

steipete/video-frames

Extract frames or short clips from videos using ffmpeg.

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steipete/summarize

Summarize or transcribe URLs, YouTube/videos, podcasts, articles, transcripts, PDFs, and local files.

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openclaw/openclaw

Use when testing, fixing, or extending the OpenClaw Control UI GUI with Vitest + Playwright end-to-end checks, mocked Gateway WebSocket flows, mocked dashboard runs, screenshots/videos, or agent-verifiable browser proof.

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obra/superpowers

Obra superpowers agent skills.

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affaan-m/ECC

See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio...

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affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

community