「theoretic」の検索結果

Use when building the exhibits of an Accounting, Organizations and Society (AOS) manuscript — data-inventory and evidence tables for qualitative work, cell-means and process-test tables for experiments, and figures that carry theoretical weight — in Elsevier-compatible format. Builds exhibits; it does not run the analysis (aos-data-analysis).

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Use when deciding which amr-* sub-skill to invoke next, or when sequencing a theory-building manuscript from theoretical-puzzle framing through developmental-review revision for an Academy of Management Review (AMR) submission. Routes — does not replace — the specialized skills.

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Use when building the theoretical engine of an Accounting, Organizations and Society (AOS) manuscript — choosing a social/organizational theory tradition (institutional theory, governmentality, Bourdieu, actor-network theory, practice theory, psychological process theory) and making it generate the analysis rather than decorate it. Builds the lens; it does not collect data (aos-methods) or frame the contribution (aos-contribution-framing).

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Use when the theoretical puzzle is the bottleneck for an Academy of Management Review (AMR) manuscript — deciding whether an idea is theory-worthy and AMR-fit before any theorizing begins. Frames the puzzle; it does NOT build constructs (that is amr-theory-development) or design any empirical study (AMR has none).

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Use when building the conceptual exhibits of an Academy of Management Review (AMR) manuscript — process models, 2x2 typologies, multi-level frameworks, and propositions tables that carry theoretical work. These are CONCEPTUAL figures, NOT data plots; AMR has no charts of results because it has no data.

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Use when turning results into an explicit theoretical contribution for an Academy of Management Journal (AMJ) manuscript — the "what new theory do we learn?" statement and the discussion section. Frames the contribution and implications; it does not build the original theory (amj-theory-development) or run the analysis (amj-data-analysis).

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Use when scoping or sanity-checking a research question for an Academy of Management Journal (AMJ) manuscript — fit, theory-drivenness, and feasibility. Decides whether the idea can earn a theoretical contribution; it does not build the theory itself (use amj-theory-development) or position the literature (amj-literature-positioning).

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Use when the theoretical argument and hypotheses are the bottleneck for an Academy of Management Journal (AMJ) manuscript — building a mechanism and deriving testable hypotheses a priori. Constructs the theory; it does not run the analysis (amj-data-analysis) or write the final contribution paragraph (amj-contribution-framing).

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Use when building or cleaning the tables and figures for an Academy of Management Journal (AMJ) manuscript — correlation tables, regression/SEM/HLM result tables, the theoretical-model figure, and interaction plots in AOM house style. Finalizes exhibits; it does not run the analysis (amj-data-analysis) or frame the contribution (amj-contribution-framing).

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Use when the research design and method are the bottleneck for an Academy of Management Journal (AMJ) manuscript — matching design (archival, survey, experiment, multi-method, field) and level of analysis to the theoretical question. Designs the study; it does not run the estimation or validity checks (amj-data-analysis).

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Use when designing or auditing AAMAS experiments - self-play and population-based training, opponent selection, equilibrium and regret metrics, game-theoretic simulations, ablations, seeds, hyperparameters, compute, and claim-to-evidence fit - with emphasis on experiments that probe the interaction rather than chase a single-agent leaderboard.

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Use for full-manuscript prose polish of an Academy of Management Journal (AMJ) manuscript — front-loading the argument, active voice, structure, and AOM house style. Polishes language and structure; it does not create the theoretical contribution (amj-contribution-framing) or fix the analysis (amj-data-analysis).

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Use when articulating and differentiating the theoretical contribution of an Academy of Management Review (AMR) manuscript — showing precisely what is NEW versus prior theory and why it matters. Frames the contribution; it does NOT build the theory (amr-theory-development) or check its internal logic (amr-data-analysis).

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Use when the front end of an Academy of Management Journal (AMJ) manuscript needs to engage the right literatures and stake a clear position in an ongoing theoretical conversation. Positions the paper among theories; it does not derive the hypotheses (amj-theory-development) or write the contribution paragraph (amj-contribution-framing).

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Enhancement-overlay SOP for adding sparse (BM25 / keyword) retrieval alongside dense (embedding) retrieval. Activate when a calling agent is building, reviewing, or debugging a retrieval pipeline whose corpus contains exact-match tokens — identifiers, error codes, SKUs, API/function names, proper nouns, citations, rare jargon — that pure dense embedding silently misses. Encodes the single decision rule (**hybrid is traffic-driven, not theoretical: add sparse only when the query share that depends on exact tokens is non-trivial**), the wiring of QueryFusionRetriever-style fusion (RRF vs alpha-weighted), and per-query-type alpha tuning. Frame the work as recovering lexical identity that dense pooling destroys, not as "add keyword search for completeness". Cross-links [[llamaindex]].

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Use for social science academic paper drafting, outlining, diagnosis, review, and revision. Trigger for topic diagnosis, research question refinement, literature review planning, CNKI/Google Scholar literature search-to-Zotero workflows, structured paper reading notes, theoretical framework design, research design critique, draft review, section or paragraph revision, citation and evidence risk checking, causal-claim checking, and pre-submission review. Do not use for purely creative writing or non-academic editing.

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Options trading strategy analysis and simulation tool. Provides theoretical pricing using Black-Scholes model, Greeks calculation, strategy P/L simulation, and risk management guidance. Use when user requests options strategy analysis, covered calls, protective puts, spreads, iron condors, earnings plays, or options risk management. Includes volatility analysis, position sizing, and earnings-based strategy recommendations. Educational focus with practical trade simulation.

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Applies the reasoning of Pieter Abbeel, robotics and reinforcement learning expert, UC Berkeley professor, and co-founder of Covariant. Use this skill whenever you are designing AI systems, tackling Sim2Real transfer, deploying machine learning in the physical world, or evaluating reinforcement learning architectures. Trigger this skill for questions about domain randomization, reward design, bootstrapping real-world AI, robotics hardware assumptions, or shifting from hard-coded rules to data-driven deep learning. It helps ground theoretical AI in physical embodiment and pragmatic deployment.

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Think and work like an expert Knowledge Representation Researcher. Use when a task calls for Knowledge Representation Researcher judgment. Reasons from model-theoretic semantics, the expressivity-vs-decidability-vs-scalability tradeoff, and competency questions through OWL 2 profiles, reasoners (HermiT, Pellet, ELK), ROBOT/Protégé pipelines, and SHACL validation while treating unsatisfiable classes, silent OWA-vs-CWA semantic mixing, hallucinated LLM-suggested axioms, and IRI-reuse on bad merges as first-class failure modes.

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Deep behavioral audit of a Lattice skill — proposes 3 review personas relevant to the skill, runs independent scenario analysis from each persona's perspective, then merges only the high-confidence, practical findings into a severity-ordered gap report with proposed fixes. Structural validation (conventions, cross-references) is skill-validate's job — this skill finds gaps that would realistically surface when someone actually uses the skill: missing scenario handling, ambiguous instructions, silent failure cases, and behavioral inconsistencies. Filters out theoretical edge cases, low-likelihood speculation, and findings owned by other skills. Use after writing or significantly changing any skill, or when the user says 'review this skill', 'deep review', 'does this skill work', 'find gaps in this skill', 'stress test this skill', 'review from different angles', or 'skill review'. Standalone — does not call other skills.

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Security audit of a codebase — web apps, APIs, services, CLI tools, libraries, daemons, and more. Use when asked to find security bugs, do a security review, audit for vulnerabilities, or pen-test the code. Focuses on exploitable issues with real impact, not theoretical concerns or industry-standard behavior.

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Applies the reasoning of Pieter Abbeel, robotics and reinforcement learning expert, UC Berkeley professor, and co-founder of Covariant. Use this skill whenever you are designing AI systems, tackling Sim2Real transfer, deploying machine learning in the physical world, or evaluating reinforcement learning architectures. Trigger this skill for questions about domain randomization, reward design, bootstrapping real-world AI, robotics hardware assumptions, or shifting from hard-coded rules to data-driven deep learning. It helps ground theoretical AI in physical embodiment and pragmatic deployment.

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Schools of historical thought, methodology debates, and the philosophy of history. Covers the major historiographical traditions (Annales, Marxist, feminist, postcolonial, subaltern, world-systems), their methodological commitments, their contributions and limitations, and the enduring debates about objectivity, narrative, and the nature of historical knowledge. Use when evaluating how different historians approach the same subject, understanding why historical interpretations change over time, or assessing the theoretical framework underlying a historical argument.

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Category-theoretic pipes with GF(3) flow balance checking. Validates data transformation pipelines using triadic trit algebra.

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。