Results for “research-planning”

Apply the OKRs framework to structure analysis, guide decision-making, and improve outcomes in product research and strategic planning contexts.

Structured planning methodology with research, brainstorming, phased plan creation, risk assessment, and plan-to-build continuity.

Plans and executes complex, multi-step research by decomposing questions, orchestrating subagents, and synthesizing findings into reports.

Routes research planning, funding, scoping, and synthesis inquiries to one of four sub-skills: clinical research, R&D finance, market research, or product research, using a deterministic decision tree.

Collaborates with users to design structured development plans broken into testable commits, with research and clarification steps.

Guides a structured planning pipeline for coding tasks, from scoping and research to plan creation, review, and handoff.

Get Shit Done - Full project planning and execution workflow. Handles project initialization with deep context gathering, automated research, roadmap creation, phase planning, and execution with verification.

Research, expand, and cluster keywords for content strategy. Use when planning content topics, building keyword lists, expanding seed keywords, clustering by topic and intent, or mapping keywords to funnel stages. Triggers on "keyword research," "keyword expansion," "keyword clustering," "content topics," "what to write about," "topic ideation," "content planning," "6 circles method," "seed keywords," "keyword difficulty," "search volume," "intent mapping," "pillar content strategy," or "content calendar planning." For SEO optimization and auditing, see seo-and-aeo-strategy.

Provides a suite of five product team skills covering OKR alignment, feature prioritization, sprint planning, user research, and design systems, with scripts and templates for each role.

Applies the TAM/SAM/SOM market sizing framework to guide decision-making, structure analysis, and produce actionable recommendations for product research.

Transforms a rough idea into a detailed design document with an implementation plan through iterative requirements clarification, research, design, and planning.

Research-driven strategist who produces content strategies, scripts, and copy. Use for competitor analysis, trend research, content planning, scripts, copywriting, or brief validation — or when the user asks for the Strategist.

Chrome-dependent academic literature scouting and idea planning. Use when the user gives a research idea, topic, question, or draft direction and wants Codex to browse Google, Google Scholar, and academic sources through the Codex Chrome plugin, identify relevant papers, explain what can be borrowed from them, and write a planNN.md before collecting PDFs or BibTeX.

Transform research findings into actionable implementation plans with stakes-based rigor, test-first strategy, and granular task decomposition.

discovery-plan

Manage R&D program budgets with F&A splits, track burn rate and runway against milestones, and route capitalize-vs-expense decisions to a named finance owner.

Design reading plans with retention strategies. TRIGGERS - Use when user needs help with reading-plan related tasks.

Plan customer discovery interviews with the right goal, segment, constraints, and method for problem validation, churn research, or new product ideas.

研究优先于编码的工作流程。在编写自定义代码之前，搜索现有的工具、库和模式。调用研究员代理。

Use when a research design spec exists and the user is ready to translate it into a concrete implementation plan with phased tasks, artifacts, and verification criteria. Produces a research execution plan organized in canonical research phases — collection, preparation, analysis, robustness, writing, submission.

Turn a refined research proposal or method idea into a detailed, claim-driven experiment roadmap. Use after `research-refine`, or when the user asks for a detailed experiment plan, ablation matrix, evaluation protocol, run order, compute budget, or paper-ready validation that supports the core problem, novelty, simplicity, and any LLM / VLM / Diffusion / RL-based contribution.

Organize research by managing references, notes, and collaboration across Google Drive, Docs, Sheets, and Gmail.

Turn a theory-first research idea into a proof-oriented research plan. Use after idea-creator-analysis, or when the user asks for theorem targets, assumptions, proof obligations, impossibility routes, analysis validation, or a non-experimental plan.

Use when a research implementation plan exists in docs/superpapers/plans/ and the user is ready to execute it — collecting data, running analysis, producing outputs, writing the paper. Orchestrates task execution with replication-driven verification and two-stage review at phase boundaries.

Guides researchers through structured ideation frameworks to discover high-impact research directions.

Plan and synthesize product/user research with method rigor: select the right method for the goal, compute defensible sample sizes with confidence labels, and cluster coded observations into insights while flagging single-source anecdotes.

Searches multiple web sources, synthesizes findings, and produces cited research reports using delegated subagents. Use when the user asks to research a topic online, search the web, look something up, find current information, compare options, or produce a research report.

Research YouTube topics, analyze competitor videos, deconstruct viral content, and query the YouTube Data API. Use when researching a video topic before planning, analyzing video transcripts for viral patterns, searching competitor channels, or fetching video and channel stats via the YouTube Data API v3.

Route research prompts to evidence, retrieval, scraping, data, market, or scientific research skills. Use when prompts mention deep research, current facts, citations, Exa, iterative retrieval, search-first, scraping, data pipelines, PubMed, USPTO, gget, literature review, or scholar evaluation.

Search external documentation (web pages, API docs, papers) and generate useful summaries for development. Use when investigating new technologies, understanding third-party APIs, researching best practices, or gathering information for technical decisions. Reduces hallucinations and expands agent knowledge.