「thesis」の検索結果

Expert-level statistics knowledge. Use when working with probability distributions, hypothesis testing, regression, Bayesian statistics, statistical inference, experimental design, ANOVA, or statistical modeling. Also use when the user mentions 'p-value', 'confidence interval', 'hypothesis test', 'regression', 'ANOVA', 'chi-square', 't-test', 'Bayesian', 'maximum likelihood', 'statistical significance', 'correlation', 'normal distribution', or 'sampling distribution'.

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。

Synthesises the current conversation context into a Product Requirements Document and publishes it to GitHub (as a comment on a referenced issue, or a new issue). Synthesises from context; does not interview. TRIGGER when: the conversation has produced enough understanding of a feature and the user wants it captured as a PRD. DO NOT TRIGGER when: a single small issue is enough → creating-issues; the idea has not been stress-tested yet → grilling-ideas first; bug reports.

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。

[Workflow] Use when activating the Research & Synthesis workflow — research a topic via web sources, then synthesize per --output={synthesis|business-eval|marketing|course} (knowledge report, business evaluation, marketing strategy, or course material).

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。

Write a single-thesis narrative newsletter essay from Ahmad's OpenMark saves. Use when Ahmad wants a thoughtful long-form piece with one clear argument, not a roundup or news recap. Trigger phrases include "essay", "long-form", "think piece", "thoughtful post", "argue that", "make a case for", "/newsletter-essay". Output is one strong thesis sentence + 3–5 narrative sections + closing call-to-think, no tables, no bullets unless necessary.

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。

Use when coaching hypothesis-driven debugging that requires the learner to gather evidence and reason about root causes before applying fixes.

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。

Builds DRAFT user personas from the research notes, interview summaries, survey free text and support themes the user provides: for each persona the goals, pains, jobs to be done, context of use, quotes exactly as supplied with their participant codes, and the evidence count behind every attribute, with names, demographics and any detail no participant stated left UNKNOWN rather than invented. Use when the user asks to "build personas from these interviews", "who are our users based on this research", "draft user personas", "turn these research notes into personas" or "update our personas with the new interviews". Do not use for theming a batch of customer feedback into counts, use customer-feedback-theme-synthesis instead; for exit interviews, use exit-interview-synthesis; for the requirements those personas imply, use product-requirements-draft. Drafts for human review; never approves, authorises or signs off.

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。

複数の AI / 人間レビュー結果 (review-self / review-external / findings-pool) を統合し、実在性・重大度・対応優先度・merge 可否を検証する。

Repository または subsystem を対象に、source-only で明示的なセキュリティ監査を行う entry skill。 通常の PR セキュリティレビューとは分離し、reconnaissance、scope 固定、既存 security skill への委譲、 evidence と unresolved hypothesis、observe-only SecurityAuditCoverage、coverage critic、 structured audit artifact と repeat-run coverage を扱う。target-controlled code は実行しない。

Use when working with Aws Cdk Deep — aWS CDK application and stack management. Covers stack synthesis, CloudFormation template inspection, diff analysis, deployment orchestration, context values, asset management, and construct library usage. Use when managing CDK apps, debugging synthesis errors, reviewing stack diffs, or analyzing deployed CloudFormation resources.

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。

Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.

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。

AiZynthFinder retrosynthetic route planning (CASP) from AstraZeneca Molecular AI. Monte Carlo tree search guided by a template-based neural expansion policy recursively disconnects a target SMILES until precursors are found in a purchasable stock. Covers config.yml (v4 format), aizynthcli batch screening, the AiZynthFinder/AiZynthExpander Python API, one-step disconnections, custom stocks via smiles2stock, scorers, Retro*/breadth-first/DFPN search alternatives, and reading output.json.gz / trees.json. Use for synthesis route planning, synthesizability screening, and building-block/precursor search. For reaction barriers use neb-irc-activation-energy; for 2D reaction scheme drawing use rdkit-chemdraw-cdxml.

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 specialist v3 — hypothesis, sample size, statistical significance, Bayesian

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。

Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, guide my research, help me think through, 研究, 深度研究, 文獻回顧, 文獻探討, 系統性回顧, 後設分析, 事實查核, 引導我的研究, 幫我釐清, 幫我想想, 我不確定要研究什麼, 研究方向, 研究主題.

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。

Performs retrosynthetic planning using AiZynthFinder (MCTS, template-based), Chemformer (template-free transformer), ASKCOS, and emerging RetroSynFormer with explicit handling of route scoring, building-block availability (eMolecules, Enamine, Mcule), forward prediction validation (Molecular Transformer), and disconnection-aware multi-objective search (MO-MCTS). Use when assessing synthetic feasibility of generated or selected molecules, planning multi-step syntheses, building synthesis-aware design pipelines, or screening libraries for retro-route feasibility.

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。

The live fieldwork layer for psycho-logic — go look at the actual target market NOW instead of reasoning from your training-data stereotype of it. Use when a psycho-logic move needs grounding in a specific place: the user asks 'what do competitors in [region/country] actually do', 'what's the real price band / norm here', 'how do local leaders position themselves', 'research this market before we localise', 'what signals trust to buyers in X', or is about to launch/adapt in a market you haven't studied. Runs structured web research in the local language — local competitors and their signals, price bands, category conventions, review/trust sources, local terminology, taboos and regulations — and synthesises a compact perception profile the four moves consume. Inspired by Rory Sutherland's *Alchemy*. Routed to from psycho-logic; pair with cultural-context (the lens that tells you what to look for). 日本語・中文の相談（「現地の実態を調べて」「调研当地市场」）にも使う。

研究文書（概要/梗概/アブストラクト・研究論文・卒業論文）を種別自動判別し、研究の骨子・グローバル一貫性・当てどころ・関連研究・説明不足・弱点・体裁の各面から一括レビューして教員向け統合1ファイルに集約するメタスキル。framing-check(骨子＋一貫性)・aim-check(当てどころ)・articulation-check(5W)・weakness-analyze(弱点)・lit-survey(関連研究)で検出し、shepherd で内容面を整形、format-check(概要は --fixed で紙面配分)で体裁を見る。--student で student-comment に渡し学生向け1枚も生成。論文・概要・卒論・中間発表予稿を「レビューして」「総合的に見て」と言われたときに使う。旧 abstract-review / paper-review / thesis-review / review を統合。

Performs retrosynthetic planning using AiZynthFinder (MCTS, template-based), Chemformer (template-free transformer), ASKCOS, and emerging RetroSynFormer with explicit handling of route scoring, building-block availability (eMolecules, Enamine, Mcule), forward prediction validation (Molecular Transformer), and disconnection-aware multi-objective search (MO-MCTS). Use when assessing synthetic feasibility of generated or selected molecules, planning multi-step syntheses, building synthesis-aware design pipelines, or screening libraries for retro-route feasibility.

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。

Generate a concise 1-page investment brief from a thesis — the elevator pitch version. Use when user says "brief", "summarise thesis", "pitch me [TICKER]", "one-pager", or "investment memo".

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。

Refresh the Key Metrics table in a thesis with current data from Financial Modeling Prep, with a Quartr standardized-statement tie-break for Revenue Growth / Gross Margin gaps (Step 4b-Q) and a scoped web-search fallback (Step 4b) when FMP has no data or resolved the wrong company. Use when user says "numbers", "refresh metrics", "update key metrics", or "refresh [TICKER]" with no other action implied. Surgical edit only — does NOT create research notes or propagate via /sync. Also flags (never auto-edits) stale price/valuation framing in the thesis Summary — see Step 10b.

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。

Refresh the Key Metrics table in a thesis with current data from Financial Modeling Prep, with a scoped web-search fallback (Step 4b) when FMP has no data or resolved the wrong company. Use when user says "numbers", "refresh metrics", "update key metrics", or "refresh [TICKER]" with no other action implied. Surgical edit only — does NOT create research notes or propagate via $sync. Also flags (never auto-edits) stale price/valuation framing in the thesis Summary — see Step 10b.

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。

Rename a thesis file when company name changes. Atomically updates filename, all inbound wikilinks across the vault, graph adjacency entry header, sector note Active Theses entry, snapshot snapshot_of references, and _hot.md mentions. Use when company changes name (FB → META, Square → Block, etc.), or when correcting a typo in a thesis filename.

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。

Weekly sweep of ALL transcript-bearing spoken events (earnings calls, conference firesides, CMDs, investor days, AGMs, investor updates) for every active thesis, via the Quartr watchlist. Produces a triage digest in Daily Intel/ flagging thesis-touching mentions and recommending deep reads. Use when user says "event sweep", "what did my companies say this week", "conference sweep", or on the weekly schedule. Also `--setup` (build/rebuild the Quartr watchlist from active theses) and `[N]` (window override in days, default 8).

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。

Extract a thesis's load-bearing assumptions and scan for internal contradictions — the falsifiable claims the bull case requires, what would falsify each, and where the thesis's own Risks / Bear Case / research already argue against it. Use when user says "assumptions", "what must be true", "load-bearing assumptions", or "does [TICKER] contradict itself".

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。

Write a rigorous, decision-grade experiment spec — falsifiable hypothesis, primary metric, guardrails, randomisation unit, exposure definition, method (A/B, holdout, switchback, quasi-experiment, MAB), MDE/duration plan, peek policy, validity threats, and pre-committed decision rule. Platform-agnostic. Load when the user has a candidate experiment and needs to spec it before launch, or says "spec this experiment", "write the test plan", "design this A/B test", "what's the hypothesis", "how big a sample do we need", "how long should we run this", "define the metrics for this test", or when the experimentation orchestrator routes here.

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。