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Produce an experiment blueprint from a research hypothesis

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Applies cognitive science frameworks for creative thinking to CS and AI research ideation. Use when seeking genuinely novel research directions by leveraging combinatorial creativity, analogical reasoning, constraint manipulation, and other empirically grounded creative strategies.

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Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction. Routes to domain-specific skills for execution, supports continuous agent operation via Claude Code /loop and OpenClaw heartbeat, and produces research presentations and papers. Use when starting a research project, running autonomous experiments, or managing a multi-hypothesis research effort.

日本語の概要は準備中です。原文の説明を表示しています。

Draft a LaTeX research paper from all previous stage outputs

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Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.

日本語の概要は準備中です。原文の説明を表示しています。

Guides researchers through structured ideation frameworks to discover high-impact research directions. Use when exploring new problem spaces, pivoting between projects, or seeking novel angles on existing work.

日本語の概要は準備中です。原文の説明を表示しています。

Search academic literature and generate research hypotheses

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Run fast, progressive experiments to map tunable parameters and their effects. Use when optimizing code, prompts, configurations, or other artifacts against a goal or benchmark, or when a long research run needs a planned hypothesis queue, focused trials, and durable findings.

日本語の概要は準備中です。原文の説明を表示しています。

Sponsor and ad-read research on podcasts and YouTube: who sponsors a show, or which shows a brand sponsors, how often, since when. Uses arcmira.

日本語の概要は準備中です。原文の説明を表示しています。

Researches a person across podcasts and YouTube for interview or meeting prep: where they appeared, their own words, who discusses them. Uses arcmira.

日本語の概要は準備中です。原文の説明を表示しています。

Record a decision, document existing code, or file a supplied research material. Modes: document decision (ADR, RFC, or rule), document code (spec, doc, guide, or scenario for existing behavior), document research (only when a finished report or one external material is already in hand). Use for 'we decided', 'record this decision', 'document why we chose X', 'make it our standard', 'draft an RFC', 'should we switch to Y' proposals, 'resolve the RFC', 'we accepted the proposal', 'document the auth module', 'capture how the payment system works', reference material, how-to instructions, or a user flow with examples over an existing spec. Name the type inside the subject to skip the type question. Planning a feature or an intended user journey → /archcore:plan. Checking docs against code or docs health → /archcore:review.

日本語の概要は準備中です。原文の説明を表示しています。

基于 instinct 的持续学习系统，通过 hooks 观察会话，创建带置信度评分的 atomic instincts， 并将高置信度 instinct 演进为 skills/commands/agents。v2.1 增加项目级 instincts 防止跨项目污染。

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Answer one cited question: how code works, or whether a repeated pattern deserves a rule. Use when: asked how, why, or whether to enforce a pattern.

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Use only after explicit Codex `$superloopy:superloopy-research` or Claude Code `/superloopy:superloopy-research` invocation, a research task started with a leading `loopy` or `루피` (such as `loopy research`), or an active Superloopy loop explicitly routing a research deliverable here. Evidence-backed Superloopy research orchestration with automatic advisory usage targets, parallel read-only lanes, per-retrieval verdicts, graded and dated sources, empirical verification, a priced claim ledger, cited synthesis, and optional reports. Do not activate from research, investigate, look-up, summarize, deep-dive, report, or similar vocabulary alone, in any language; ordinary questions, debugging, and implementation context-gathering stay with their primary workflows.

日本語の概要は準備中です。原文の説明を表示しています。

Codex-native multi-keyword Amazon opportunity scan using LaunchFast MCP. Use when the user wants to research 1-10 keywords, compare niches, or decide whether a product idea is a GO, INVESTIGATE, or PASS. Requires the LaunchFast MCP tool `research_products`.

日本語の概要は準備中です。原文の説明を表示しています。

Deep Codex-native Amazon FBA product validation using LaunchFast MCP and the LegacyX criteria. Use when the user wants a serious viability review for a keyword, niche, or adjacent niche expansion.

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Codex-native batch Amazon keyword research using LaunchFast MCP. Use when the user wants a ranked comparison across many keywords and optionally wants HTML and CSV artifacts written to disk.

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Codex-native supplier sourcing and outreach workflow for Alibaba using LaunchFast research. Use when the user wants supplier shortlists, outreach messages, reply triage, or negotiation support. Requires `supplier_research`. Browser automation is optional but useful when the user wants Codex to interact with Alibaba directly.

日本語の概要は準備中です。原文の説明を表示しています。

Codex-native Amazon PPC keyword research using LaunchFast MCP. Use when the user wants competitor keyword discovery, keyword tiering, or a ready-to-upload Amazon Sponsored Products bulk file from 1-15 ASINs. Requires the LaunchFast MCP tool `amazon_keyword_research`.

日本語の概要は準備中です。原文の説明を表示しています。

End-to-end Codex-native Amazon FBA research workflow using LaunchFast MCP. Use when the user wants a single report covering product research, IP risk, supplier sourcing, and PPC keyword intelligence. Requires `research_products`, `ip_check_manage`, `supplier_research`, and `amazon_keyword_research`.

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Entry point for new or resumed work. Researches and scopes new tasks; validates and resumes handoff/checkpoint manifests. Triggers: start, begin, do, implement, build, fix, create, resume, continue.

日本語の概要は準備中です。原文の説明を表示しています。

Record a decision, document existing code, or file a supplied research material. Modes: document decision (ADR, RFC, or rule), document code (spec, doc, guide, or scenario for existing behavior), document research (only when a finished report or one external material is already in hand). Use for 'we decided', 'record this decision', 'document why we chose X', 'make it our standard', 'draft an RFC', 'should we switch to Y' proposals, 'resolve the RFC', 'we accepted the proposal', 'document the auth module', 'capture how the payment system works', reference material, how-to instructions, or a user flow with examples over an existing spec. Name any document type inside the subject — journey, prd, idea, or cpat included — to get exactly that type. Planning a feature or an unnamed intended user journey → /archcore:plan. Checking docs against code or docs health → /archcore:review.

日本語の概要は準備中です。原文の説明を表示しています。

中文学习教练技能。用于学习编程、英语、设计、产品、AI、数学或任何技能时，先诊断水平，再用讲解、练习、反馈、复习的循环推进。触发语包括"进入学习模式""我想学""带我练""帮我制定学习计划""像教练一样教我"。

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Finds free backlink and brand mention opportunities across Hacker News, Quora, GitHub, directories, and niche communities. Outputs a prioritized action plan with draft responses ready to post. Use after brand research and content creation to amplify reach and AI engine citations.

日本語の概要は準備中です。原文の説明を表示しています。