Audit existing experimentation infrastructure and past experiments for methodology issues. Use when asked to "audit our experiments", "is our experimentation sound", or "review past test methodology".
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。
876 件 ・ 関連度順
概要と使いどころ
Audit existing experimentation infrastructure and past experiments for methodology issues. Use when asked to "audit our experiments", "is our experimentation sound", or "review past test methodology".
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。
Audit feature engineering code for leakage, quality issues, and pipeline correctness. Use when asked to "audit our feature pipeline", "is there data leakage", or "find feature quality issues".
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。
Audit existing data cleaning code — find missing validation, silent data loss, and quality gaps. Use when asked to "audit our data cleaning", "are we losing data silently", or "find data quality gaps".
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。
Design a data validation pipeline — schema checks, range validation, and quality metrics. Use when asked to "validate incoming data", "add schema checks", or "define data quality metrics".
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。
Survey existing forecasting code or models in a codebase — find gaps, stale models, and missing validation. Use when asked "what forecasting models do we have", "audit our forecasts", or "find stale models".
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。
Validate and benchmark a forecasting model — walk-forward CV, error metrics, baseline comparison. Use when asked "is this forecast any good", "validate a forecasting model", or "backtest the forecast".
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。
Build a forecasting model for a time series — demand, revenue, or usage prediction. Use when asked to "forecast demand", "predict next quarter revenue", or "build a time series model".
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。
Design a data cleaning and transformation pipeline — missing values, outliers, and deduplication. Use when asked to "clean this dataset", "handle missing values", or "deduplicate this data".
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。
Batch download academic paper full-text (PDF/XML) from a list of DOIs. Handles 25 DOI prefixes across 19 publisher families via three layered routes: (1) publisher TDM APIs requiring institutional subscription (Elsevier ScienceDirect, Wiley Online, Springer Nature), (2) Open Access sources (Crossref, Unpaywall, OpenAlex), and (3) a browser-based fallback for paywalled publishers without TDM access (ACS, RSC, IEEE, AIP, IOP, APS, Annual Reviews, T&F, Chinese journals). Browser fallback offers two routes — Route A drives the user's logged-in Chrome via the OpenClaw `browser` tool with `profile="user"` (best for interactive sessions), Route B uses the standalone `auto-paper-harvester` CLI with its built-in Playwright (best for unattended bulk runs). Use when the user wants to harvest, scrape, fetch, or bulk-download papers from a DOI list, savedrecs export, or Excel; or wants to fill missing full-text PDFs for an existing literature collection. Triggers on phrases like "批量下载文献", "下载全文", "harvest papers", "scrape full text", "TDM API", "下载 Elsevier 全文", "Wiley 批量下载", "下载 PDF".
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。
How nutrition science becomes dietary guidance, and how industry, agriculture, and politics shape that process. Covers the US Dietary Guidelines cycle, food labeling, WIC and SNAP, commodity subsidies, and the documented history of industry influence on research and recommendations. Use when a question asks why a guideline says what it says, how a recommendation got written, or whether an industry-funded study should be trusted.
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。
Vocabulary learning strategies and retention science for any language -- frequency-based word selection, spaced repetition systems (Ebbinghaus forgetting curve, Leitner system, SM-2 algorithm), cognate exploitation, word family networks, context-based learning, collocations, depth of word knowledge (form, meaning, use), reading progression from controlled to authentic texts, and productive vs. receptive vocabulary thresholds. Use when building vocabulary plans, optimizing review schedules, selecting learning materials, or diagnosing vocabulary gaps.
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。
Birding by sight and sound — gestalt, song and call vocabulary, behavioral and habitat clues, and the discipline of producing eBird-grade records. Covers the vocabulary of bird field marks, the primary categories of vocalization, the habits of habitat-filtering, and the protocol for submitting records to a citizen-science database without degrading data quality. Use when the task is bird-specific observation or record-keeping.
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。
Human modification of Earth's systems and the geographic dimensions of environmental change. Covers climate change science (greenhouse effect, feedback loops, projections), deforestation and land use change, desertification and soil degradation, water resource management, biodiversity loss and conservation geography, pollution and environmental justice, and sustainability frameworks. Use when reasoning about human impacts on the environment, environmental policy, conservation planning, climate adaptation, or the spatial distribution of environmental risks.
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。
Earth systems science covering plate tectonics, landforms, erosion, biomes, hydrosphere, atmospheric circulation, and the interactions among lithosphere, hydrosphere, atmosphere, and biosphere. Provides frameworks for analyzing how physical processes shape landscapes over geological and human timescales. Use when reasoning about landforms, natural hazards, climate patterns, ocean currents, biogeography, or any question about how Earth's physical systems operate and interact.
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。
Bias detection and mitigation, fairness metrics, privacy frameworks, consent models, transparency requirements, and accountability structures for data science practice. Covers algorithmic bias sources, disparate impact testing, differential privacy, GDPR principles, model cards, datasheets for datasets, responsible AI frameworks, and the organizational governance needed to make ethics actionable. Use when auditing models for bias, designing privacy-preserving systems, establishing governance processes, or evaluating the social impact of data-driven decisions.
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。
A/B testing, randomization, sample size calculation, confounding control, and causal inference for data science. Covers the full experimental lifecycle from hypothesis formulation through power analysis, randomization strategies, blocking, factorial designs, sequential testing, and the potential outcomes framework for causal claims. Use when designing experiments, planning A/B tests, calculating sample sizes, or reasoning about causation from data.
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。
Efficient database search tool for bioRxiv preprint server. Use this skill when searching for life sciences preprints by keywords, authors, date ranges, or categories, retrieving paper metadata, downloading PDFs, or conducting literature reviews.
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。
Start-of-session situational report for a research or code repository. Reads the handoff, log, or status files the project actually keeps, checks live git state, and reports the objective, verified baseline, open tasks, blockers, and next actions, flagging where the documents and the repository disagree. Use when resuming work after time away or before changing anything. Its end-of-session twin is finished.
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-of-session closure for a research or code repository. Records what changed into the project's own handoff and log files, separating verified work from work merely attempted, and reports what is left uncommitted. Use when wrapping up a session so the next one can resume without re-deriving state. Its start-of-session twin is sitrep.
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。
Opens a deliverable (talk, course module, paper, book chapter, or referee report) for AI-assisted work across sessions. Interviews the author for the manifest, then scaffolds deliverable.yml, an append-only HANDOFF.md, a numbered planning/ wiki with open questions, an inbox/ for dictated braindumps, a gitignored checks/, and the house deck template for talks. Use when starting deadline-driven work that spans sessions, or when asked to open a deliverable, set up a talk, paper, or module for the pipeline, or make a manifest. Not for one-off tasks.
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。
Reviews a whole deliverable (talk, course module, paper, chapter, or referee report) against its manifest without rewriting it. Runs a deterministic gate for build, citations, numbers, facts, and leaks and stops on failure, then runs a finder over each section and a strong-model pass over the whole work, and adjudicates into checks/<date>/findings.json and report.md with anchored findings, severities, and honest NOT CHECKED coverage within a dollar budget. Use when asked to lint or review the whole talk, module, or paper, for a pre-ship review, or for the night shift. Revision stays serial and author-led.
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。
Turns raw captures (dictated braindumps in a deliverable's inbox/, or recent macwhspr dictation-log entries) into proposed planning-wiki changes, shown as one unified diff. Classifies each statement as a decision, evidence claim, question, task, or dropped item, traces it to its capture paragraph, tags unconfirmed names, numbers, and citations UNRESOLVED, and writes decisions only with the author's assent. Edits only the planning wiki, never source files. Use when asked to intake, absorb notes, or process the inbox, or after dictating notes from a talk, meeting, or reading session.
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。
Interviews a researcher in rounds until an idea, design, or draft has no unexamined decision — numbered questions, each with why it matters and a recommended answer, facts looked up rather than asked, and settled decisions written to a file. Stages are idea (topic or hunch to a falsifiable question and contribution claim), design (estimand, identification, sample and power, measurement, analysis plan, pre-registration, venue), and defend (reviewer objections to a finished design or draft). Use when the user says "grill me", asks to stress-test or poke holes in an idea, design, or plan, asks what they are assuming, or brings an idea that is not yet a design. --plan grills software or process plans.
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。
Spawn full peer Codex or Claude sessions in their own panes and git worktrees — real sessions, not subagents — briefed by the lead and merged back. Not for bounded consults a subagent covers. Use when work must outlive or run beside this session, needs its own worktree, or must stay user-steerable.
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。