メニュー
Adaptive Mode Mejorado - Orquestacin inteligente con DAG dinmico, feedback loops automticos y rollback inteligente. Coordina mltiples agentes con dependencias reales, permite ciclos de retroalimentacin (QA DEV QA) y ejecuta rollback automtico ante fallos crticos.
"Multi-perspective academic paper review with dynamic reviewer personas. Simulates 5 independent reviewers (EIC + 3 peer reviewers + Devil's Advocate) with field-specific expertise. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy."
"12-agent academic paper writing pipeline. 10 modes (full/plan/outline/revision/revision-coach/abstract/lit-review/format-convert/citation-check/disclosure). 6 paper types, 5 citation formats, bilingual abstracts, LaTeX/DOCX-via-Pandoc/PDF output. Style Calibration + Writing Quality Check + Anti-Patterns with IRON RULE markers. Triggers: write paper, academic paper, guide my paper, parse reviews, AI disclosure, 寫論文, 學術論文, 引導我寫論文, 審查意見."
"Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory integrity verification, two-stage peer review, and reproducible quality gates. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow."
Trigger: enforce norms, learn norms, validate documentation placement, check adaptive rules, run norm enforcer, update learned norms. Autonomous norm enforcement and learning system with 5 self-healing layers.
Vercel AI SDK 5 patterns: streaming, AI objects, tools, messages. Trigger: "AI SDK", "AI SDK 5", "streamText", "generateText", "AI provider".
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
| name | adaptive-mode-orchestrator |
| description | > |
El Adaptive Mode Orchestrator es un sistema de orquestacin inteligente que:
PLANNING (BA)
DESIGN (SAD)
IMPLEMENTATION (DEV)
GOVERNANCE (GOV) [paralelo]
DOCUMENTATION (DOC) [paralelo]
QUALITY_ASSURANCE (QA)
Si falla FEEDBACK LOOP IMPLEMENTATION
Si falla seguridad FEEDBACK LOOP GOVERNANCE
Si pasa DEPLOYMENT
DEPLOYMENT (OPS)
Si falla AUTO-ROLLBACK
Si pasa COMPLETE
config/adaptive-dag-config.json{
"versión": "1.0",
"enabled": true,
"dag": {
"agents": {
"BA": { "name": "Business Analyst", "dependencies": [] },
"SAD": { "name": "Solution Architect", "dependencies": ["BA"] },
"DEV": { "name": "Developer", "dependencies": ["SAD"] },
"QA": { "name": "QA Engineer", "dependencies": ["DEV"] },
"OPS": { "name": "DevOps Engineer", "dependencies": ["QA"] },
"GOV": { "name": "Governance", "dependencies": ["DEV", "QA"] },
"DOC": { "name": "Documentation", "dependencies": ["DEV", "QA"] }
},
"feedback_loops": {
"qa_to_dev": {
"source": "QA",
"target": "DEV",
"trigger": "test_failure",
"max_iterations": 3
},
"gov_to_dev": {
"source": "GOV",
"target": "DEV",
"trigger": "security_issue",
---
> **Referencia detallada**: [
eferences/detail.md](references/detail.md)