SirNosh/bmad-ml - 2페이지

bmad-ml-research-party

Run multi-agent research discourse session. Use when the user requests to "start a research party" or "run a journal club".

원문 언어: 영어

bmad-ml-astra

Interdisciplinary synthesis and cross-domain transfer specialist. Use when the user asks to talk to Astra, requests the synthesizer, or needs cross-field insight connections and multi-modal research directions.

원문 언어: 영어

bmad-ml-breach

Experimental methodology and statistical rigor specialist. Use when the user asks to talk to Breach, requests the methodologist, or needs experiment design review, ablation planning, and reproducibility protocols.

원문 언어: 영어

bmad-ml-cypher

Dataset analysis and data quality specialist. Use when the user asks to talk to Cypher, requests the data detective, or needs dataset assessment, bias analysis, and benchmark evaluation.

원문 언어: 영어

bmad-ml-fade

Frontier research tracking and trend scouting specialist. Use when the user asks to talk to Fade, requests the scout, or needs arxiv monitoring, paradigm shift detection, and emerging method analysis.

원문 언어: 영어

bmad-ml-killjoy

Systems ML and hardware-aware optimization specialist. Use when the user asks to talk to Killjoy, requests the systems researcher, or needs compute-aware architecture tradeoffs, distributed training, and inference optimization.

원문 언어: 영어

bmad-ml-sage

Mathematical foundations and theory specialist. Use when the user asks to talk to Sage, requests the theorist, or needs mathematical analysis, proofs, and convergence guarantees.

원문 언어: 영어

bmad-ml-sova

Literature survey and SOTA tracking specialist. Use when the user asks to talk to Sova, requests the research tracker, or needs literature review, citation mapping, and paper analysis.

원문 언어: 영어

bmad-ml-viper

Adversarial robustness and ML safety specialist. Use when the user asks to talk to Viper, requests the adversary, or needs failure mode analysis, attack surface review, and robustness evaluation.

원문 언어: 영어

bmad-ml-dataset-discovery

Assess and compare candidate datasets. Use when the user requests to "find datasets" or "run dataset discovery".

원문 언어: 영어

bmad-ml-feasibility-study

Assess technical feasibility with risk analysis. Use when the user requests to "run a feasibility study" or "assess feasibility".

원문 언어: 영어

bmad-ml-literature-review

Produce citation-backed literature review artifact. Use when the user requests to "create a literature review" or "review the research literature".

원문 언어: 영어

bmad-ml-problem-formulation

Define problem statement and research hypotheses. Use when the user requests to "formulate the problem" or "define the problem statement".

원문 언어: 영어

bmad-ml-ai-product-brief

AI product brief creation workflow. Use when the user requests to create the AI Startup PRD-equivalent, define product vision, or document AI problem and approach.

원문 언어: 영어

bmad-ml-agent-behavior-spec

Agent behavior contract and guardrail specification. Use when the user requests to define agent behavior, set response boundaries, or specify behavior contracts.

원문 언어: 영어

bmad-ml-agent-system

Multi-agent system design and orchestration planning. Use when the user requests to design a multi-agent system, plan agent roles, or define coordination patterns.

원문 언어: 영어

bmad-ml-ai-readiness-check

AI implementation readiness assessment workflow. Use when the user requests to check AI readiness, assess implementation preparedness, or run a readiness audit.

원문 언어: 영어

bmad-ml-ai-system-architecture

End-to-end AI system architecture design. Use when the user requests to design AI system architecture, plan AI infrastructure, or define system topology.

원문 언어: 영어

bmad-ml-ai-ux-design

AI interaction pattern and UX safeguard design. Use when the user requests to design AI UX, plan interaction patterns, or define UX safeguards.

원문 언어: 영어

bmad-ml-data-integration

Data ingestion and integration architecture design. Use when the user requests to design data integration, plan data pipelines, or architect data ingestion.

원문 언어: 영어

bmad-ml-guardrails-design

Safety guardrail and refusal policy design. Use when the user requests to design guardrails, define refusal policies, or plan safety mitigation controls.

원문 언어: 영어

bmad-ml-prompt-engineering

Prompt strategy and template design workflow. Use when the user requests to design prompts, create prompt templates, or plan prompt iteration strategy.

원문 언어: 영어

bmad-ml-rag-pipeline

RAG pipeline design and specification workflow. Use when the user requests to design a RAG pipeline, plan retrieval strategy, or architect document retrieval.

원문 언어: 영어

bmad-ml-tool-calling-design

Tool calling schema and safety contract design. Use when the user requests to design tool calling schemas, define tool contracts, or plan invocation safety rules.

원문 언어: 영어

bmad-ml-ai-implement

Multi-component AI system implementation workflow. Use when the user requests to implement an AI system, build AI components, or integrate AI subsystems.

원문 언어: 영어

bmad-ml-build-llm-app

LLM application implementation from architecture spec. Use when the user requests to build an LLM app, implement LLM architecture, or develop an LLM application.

원문 언어: 영어

bmad-ml-doc-processing

Document ingestion and processing pipeline implementation. Use when the user requests to build a document pipeline, implement doc processing, or set up ingestion workflows.

원문 언어: 영어

bmad-ml-embedding-pipeline

Embedding generation pipeline implementation workflow. Use when the user requests to build an embedding pipeline, implement embeddings, or set up embedding quality controls.

원문 언어: 영어

bmad-ml-fine-tuning

Fine-tuning pipeline and evaluation setup workflow. Use when the user requests to fine-tune a model, build a training pipeline, or set up fine-tuning evaluation.

원문 언어: 영어

bmad-ml-quick-ai-prototype

Time-boxed AI prototype for rapid validation. Use when the user requests to build a quick AI prototype, create a rapid validation, or develop a time-boxed proof of concept.

원문 언어: 영어

bmad-ml-vector-db-setup

Vector database configuration and setup workflow. Use when the user requests to set up a vector database, configure indexes, or implement retrieval operations.

원문 언어: 영어

bmad-ml-ai-cicd

CI/CD pipeline design for AI artifacts. Use when the user requests to design AI CI/CD, build a deployment pipeline, or automate AI artifact delivery.

원문 언어: 영어

bmad-ml-ai-deploy

AI system deployment with runbook planning. Use when the user requests to deploy an AI system, create a deployment runbook, or plan rollback strategy.

원문 언어: 영어

bmad-ml-ai-evaluation

AI quality evaluation benchmark execution workflow. Use when the user requests to evaluate AI quality, run benchmarks, or compare model performance.

원문 언어: 영어

bmad-ml-ai-monitoring

AI runtime monitoring and alerting setup. Use when the user requests to set up AI monitoring, configure alerting, or design runtime observability.

원문 언어: 영어

bmad-ml-ai-product-review

AI product release readiness review workflow. Use when the user requests to review AI product readiness, assess release criteria, or evaluate launch preparedness.

원문 언어: 영어

bmad-ml-ai-regression-tests

AI regression test suite creation workflow. Use when the user requests to create AI regression tests, build test suites, or define regression coverage.

원문 언어: 영어

bmad-ml-ai-safety-audit

AI safety audit with risk-ranked findings. Use when the user requests to run a safety audit, assess AI risks, or conduct a safety review.

원문 언어: 영어

bmad-ml-ai-scaling

AI scaling strategy for performance and cost. Use when the user requests to plan AI scaling, optimize latency and throughput, or define cost-performance strategy.

원문 언어: 영어

bmad-ml-ai-sprint

AI sprint planning and progress tracking. Use when the user requests to break approved AI design into implementation work, plan an AI sprint, track sprint progress, or manage AI development iterations.

원문 언어: 영어