「planning」の検索結果

Sample-size and statistical power calculations for planning studies. Use whenever someone asks "how many subjects/samples/replicates do I need", wants an a priori power analysis, a minimum detectable effect (MDE), a power curve, or needs to justify a sample size for a grant, IRB protocol, or pre-registration. Covers closed-form power for t-tests, ANOVA, proportions, correlations, chi-square, and regression, plus simulation-based (Monte Carlo) power for designs with no formula — logistic/Poisson regression, mixed models, cluster-randomized trials, survival, and interactions. Use this skill even when the request only mentions an effect size, alpha, or "80% power" without saying "power analysis" explicitly. For laying out the study (randomization, blocking, factorial/DOE, crossover, sequential designs) use experimental-design; for analyzing data already collected and reporting it use statistical-analysis.

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Design experiments and studies BEFORE data is collected — choosing a design, randomizing, blocking, and laying out treatment combinations so the results will actually be interpretable. Use whenever someone is planning a study, asks how to assign subjects/samples to groups, mentions randomization, blocking, stratification, controls, factorial or fractional-factorial designs, design of experiments (DOE), screening many factors, response-surface optimization, crossover or repeated-measures or split-plot designs, cluster/group randomization, Latin squares, plate layouts, batch/run-order effects, replication vs. pseudoreplication, or sequential/adaptive/group-sequential designs. Trigger this even for informal phrasings like "how should I set up this experiment", "how do I avoid confounding", "what's the best way to test these 6 factors", or "assign these mice to conditions". For computing the sample size or power once the design is chosen, use statistical-power; for analyzing data already collected, use statistical-analysis.

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Creative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific observations yet. For formulating testable hypotheses from data use hypothesis-generation.

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Programmatic SEO planning and audit: building or evaluating large sets of template-generated pages that target long-tail query patterns (e.g. "[service] in [city]", "[product] vs [product]", "[tool] for [use-case]"). Covers data-source and template design, thin/duplicate-content and doorway-page risks, per-page uniqueness and value thresholds, internal linking and hubs, indexation management (publish vs. noindex), and scaling without a manual action. Use whenever the user wants to generate many pages from a template/dataset, build location/comparison/use-case pages at scale, or asks why generated pages aren't indexing. Trigger on: "programmatic SEO", "pSEO", "generate pages at scale", "templated pages", "location pages at scale", "comparison pages", "[city] pages", "my generated pages aren't indexed", "doorway pages", "scale content". For one-off content use /content-writer; for keyword discovery use /keyword-research.

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Review tutti git diffs for project structure, layering, module ownership, and duplicate event-center infrastructure by planning focused architecture review tasks, then having the main agent orchestrate sub-agents for only the changed areas.

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Analyze implementation gap between requirements and existing codebase. Use when planning integration with existing systems.

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Break down implementation plans into actionable task lists. Use after planning to create a structured task breakdown. Generates tasks.md with ordered, dependency-aware tasks.

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Use when planning an end-to-end scholarly publishing workflow, including manuscript source-of-truth, submission assets, revision/rebuttal files, camera-ready checks, reproducible build expectations, and publication package structure.

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Structured clarification workflow for underspecified requirements. Use before planning to resolve ambiguities through coverage-based questioning. Records answers in spec clarifications section.

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Pull the ads a competitor is running right now on Meta (Facebook/Instagram) and Google, then extract the hooks, offers, CTAs and landing pages worth modelling. Use when writing ad copy, planning creative tests, choosing a landing page angle, or when the user asks "what is X advertising", "what ads does X run", "find competitor ad hooks". Reads live Ad Library and Ads Transparency data through the Tracetify MCP; falls back to a manual Ad Library walkthrough when the connector is absent.

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Execute a trivial task inline — no subagents, no planning overhead

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Analyze codebase with parallel mapper agents to produce .planning/codebase/ documents

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Gather phase context through adaptive questioning before planning. Use --all to skip area selection and discuss all gray areas interactively. Use --auto to skip interactive questions (Claude picks recommended defaults). Use --chain for interactive discuss followed by automatic plan+execute. Use --power for bulk question generation into a file-based UI (answer at your own pace).

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Build, query, and inspect the project knowledge graph in .planning/graphs/

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Surface Claude's assumptions about a phase approach before planning

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Import a GSD-2 (.gsd/) project back to GSD v1 (.planning/) format

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Query, inspect, or refresh codebase intelligence files in .planning/intel/

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Create a clean PR branch by filtering out .planning/ commits — ready for code review

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Create an isolated workspace with repo copies and independent .planning/

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Diagnose planning directory health and optionally repair issues

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Activate this skill for ANY future-oriented question. Triggers include: "Will [X]?", "Who will win [X]?", "What happens to [X]?", "Can [X] succeed?", "What's the future of X?", foresight analysis, scenario planning, STEEEP analysis, futures cone, prediction requests, or any question about a future outcome. Year is NOT required — the engine infers the horizon. Also activate when the user says "predict", "forecast", "what are the odds", "scenario analysis", or asks about competitive races, technology adoption, geopolitical shifts, or market dominance. REQUIRES web search to be enabled — if web search is unavailable, tell the user before proceeding.

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Portfolio dashboard for all GSD-tracked projects. Scans ~/Projects and ~/gsd-workspaces for .planning/ directories, shows phase status, git state, blockers, and next actions for every project. Run /ops projects to see the full portfolio.

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Plan NVIDIA Parabricks pbrun commands, translate CPU options and check runtime readiness. Use for individual tools, including planning-only questions.

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Use when planning, debugging, tuning, evaluating, exporting, or deploying public Nemotron `embed`/`rerank` retrieval recipes.

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