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Claude Skills by brycewang-stanford

github.com/brycewang-stanford
5,322 skillsA× 5,279B× 42D× 129 installs5,832 views
Fcr Literature PositioningA

Use when positioning a Field Crops Research (FCR) manuscript against the agronomy and crop-science literature so it reads as a general contribution to field-crop science, not a local report. FCR requires new scientific insight of general relevance and rejects corroborative or merely descriptive work, so the literature must establish the gap and the agronomic stakes. Stakes the contribution; it does not write the lit review.

ai-agentsgo
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Fcr Reporting And Data PolicyA

Use when preparing the reporting completeness and research-data materials for a Field Crops Research (FCR) manuscript. FCR requires a data-availability statement at submission, full agronomic reporting (cultivar, soil, weather vs. phenology, management, design), declaration of any generative-AI use, and supports data/methods co-submission to Data in Brief / MethodsX. Prepares the materials; it does not waive requirements.

ai-agentsgo
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Fcr Review ProcessA

Use to understand how Field Crops Research (FCR) evaluates a manuscript — initial editor screening against the journal's scope boundary, the single-anonymized review model with typically two or more reviewers, and the common reasons for desk rejection (controlled-environment-only, single-site single-season, descriptive/local, out-of-scope species). Sets expectations and shapes the paper to survive review; it does not contact editors.

ai-agentsgo
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Fcr Revision And RebuttalA

Use when writing the response to a Field Crops Research (FCR) revision decision (major or minor) and revising the manuscript. FCR reviewers commonly press on scope/generality, statistics and G×E, reproducibility detail, and a discussion that interprets rather than repeats. The response must address every point while protecting the contribution. Structures the response letter; it does not fabricate new results.

ai-agentsgoapi
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1,052
Fcr SubmissionA

Use when running the final pre-submission preflight for Field Crops Research (FCR) via Editorial Manager — article-type selection, abstract (~400 words) and highlights (3-5 bullets of <=85 characters), complete agronomic reporting, data-availability statement, generative-AI declaration, Elsevier formatting, and the cover letter. Final checks; it does not draft content.

ai-agents
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1,052
Fcr Topic SelectionA

Use when deciding whether an agronomy or crop-science project fits Field Crops Research (FCR) and which article type to target. FCR's defining test is field-based agronomic significance with multi-season/-environment relevance — it rejects controlled-environment-only, single-site single-season, horticultural/woody-perennial, and corroborative/descriptive/local-only work. Helps frame the question; it does not collect data.

ai-agents
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1,052
Fcr WorkflowA

Use as the entry point for any Field Crops Research (FCR) manuscript. Routes to the right FCR sub-skill based on where you are in the lifecycle and which article type (Original Research Paper, Review, Short Communication, Opinion, Loomis Review) fits. It checks scope-fit first — FCR rejects controlled-environment-only and single-site single-season work — then dispatches; it does not draft content.

ai-agentsgo
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Fcr Writing StyleA

Use when drafting or polishing a Field Crops Research (FCR) manuscript so it reads for a general agronomy/crop-science audience, follows FCR structure, and meets the format expectations (abstract ~400 words, 3-5 highlights of <=85 characters, grammatically sound English, concise results, a discussion that interprets rather than repeats). Tightens prose and format; it does not invent content.

ai-agents
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1,052
Geb Contribution FramingA

Use when the "what does this advance in game theory?" sentence is missing or muddy for a Games and Economic Behavior (GEB) manuscript. Forges the single-sentence contribution and the introduction's claim structure so the Editor in Charge sees the advance immediately.

ai-agents
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1,052
Geb Data AnalysisA

Use when a Games and Economic Behavior (GEB) manuscript involves experimental data or numerical illustration — analyzing strategic-game experiments and building verified worked examples. Adapts analysis to GEB's game-theory nature, where data supports the theory rather than carrying a causal claim.

ai-agents
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1,052
Geb Identification StrategyA

Use when the analytical core of a Games and Economic Behavior (GEB) manuscript is the bottleneck — assumptions, theorem statements, proof exposition, and generality for a game-theory paper (and the experimental-identification analogue for behavioral work). Stress-tests the argument's correctness, tightness, and readability.

ai-agents
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1,052
Geb Literature PositioningA

Use when positioning a game-theory manuscript against the existing literature for Games and Economic Behavior (GEB) — staking what is new relative to known solution concepts, theorems, mechanisms, and prior experiments. Sharpens the contribution; it is not a standalone survey.

ai-agentsgo
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1,052
Geb RebuttalA

Use after a Games and Economic Behavior revise-and-resubmit to organize responses on theory novelty, equilibrium/proof details, experiments, simulations, Editor-in-Charge priorities, and Elsevier revision files.

ai-agentsgo
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1,052
Geb Replication And Data PolicyA

Use when planning data and code sharing for a Games and Economic Behavior (GEB) manuscript. GEB encourages but does NOT mandate a replication archive — unlike AER/Econometrica/JAE — so this skill helps you share well voluntarily and avoid assuming requirements that do not exist here.

ai-agentspythongo
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1,052
Geb Review ProcessA

Use when you need to understand how Games and Economic Behavior (GEB) actually evaluates a paper — the Editor-in-Charge model, anonymous Advisory Editors and referees, desk-reject and acceptance odds — so you can target the right audience and set expectations. Explains the process; it does not draft content.

ai-agents
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1,052
Geb SubmissionA

Use when running the final pre-submission preflight for Games and Economic Behavior (GEB) via Elsevier Editorial Manager — Word/LaTeX (elsarticle) source, 250-word abstract, the mandatory conference-version disclosure in the cover letter, and the generative-AI declaration. Final checks; it does not draft content.

ai-agentsgo
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Geb Tables FiguresA

Use when building exhibits for a Games and Economic Behavior (GEB) manuscript — payoff matrices, extensive-form game trees, equilibrium/result tables, and experimental plots. Makes strategic structure and results readable to a game-theory audience.

ai-agents
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1,052
Geb Topic SelectionA

Use when judging whether a game-theory result is the right fit and scale for Games and Economic Behavior (GEB) — does it advance the frontiers of game theory and its applications? Tests the idea against GEB's specialist-but-general-interest bar before the paper is built out.

ai-agents
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Geb WorkflowA

Use when deciding which geb-* sub-skill to invoke next, or when sequencing manuscript work from topic selection through rebuttal for a Games and Economic Behavior (GEB) submission. Routes — it does not replace — the specialized skills.

ai-agentsgo
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Geb Writing StyleA

Use when polishing prose, abstract, and introduction for a Games and Economic Behavior (GEB) manuscript so the model and result land for a general game-theory reader. Enforces the 250-word abstract cap and elsarticle conventions. Polishes exposition; it does not change results.

ai-agentsgo
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1,052
Gcb Cover LetterA

Use when writing the cover letter for a Global Change Biology (GCB) submission. The letter must convince the editor, in a paragraph or two, that the paper shows a mechanistic global-change advance of broad relevance that fits GCB's scope and article type. Structures the letter; it does not overstate the findings.

ai-agents
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1,052
Gcb Data AnalysisA

Use when executing and reporting the analysis for a Global Change Biology (GCB) manuscript — mixed/hierarchical models, time-series and spatial analysis, meta-analysis, and model evaluation with honest uncertainty. GCB reviewers and data archiving demand reproducible, well-quantified inference. Guides analysis norms; it does not fabricate results.

ai-agents
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1,052
Gcb Figures And TablesA

Use when building figures, tables, and the mandatory graphical abstract for a Global Change Biology (GCB) manuscript. GCB rewards mechanism-first, self-contained, accessible exhibits and requires a graphical abstract depicting the driver-to-response link. Guides exhibit design; it does not invent data.

ai-agents
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1,052
Gcb Literature PositioningA

Use when positioning a Global Change Biology (GCB) manuscript in the literature so it reads as a global-change advance, not a local report. GCB readers span ecology, biogeochemistry, and Earth-system science, so the paper must engage the cross-system literatures it speaks to. Structures positioning; it does not fabricate citations.

ai-agents
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1,052
Gcb Reporting And Data PolicyA

Use when preparing the data availability statement and the data/code archive for a Global Change Biology (GCB) manuscript. GCB requires data and code to be archived in a public repository with a persistent DOI as a condition of publication, and "available on request" is not accepted. Prepares the deposit; it does not waive requirements.

ai-agentsgogit
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1,052
Gcb Review ProcessA

Use to understand how a Global Change Biology (GCB) manuscript is judged — high desk-rejection screening for scope and significance, expert single-anonymous peer review with 2–3 reviewers, and the decision categories. Sets expectations and informs preparation; it does not contact editors or predict outcomes.

ai-agentsgo
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1,052
Gcb Revision And RebuttalA

Use when writing the response to a Global Change Biology (GCB) revise decision. A revision must address every reviewer point with evidence, defend the global-change mechanism and uncertainty treatment, and keep the archived data/code in sync. Structures the response letter; it does not fabricate new results.

ai-agentsgo
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Gcb Study DesignA

Use when designing the study behind a Global Change Biology (GCB) manuscript — manipulative experiments, observational/gradient studies, or process modelling of biological responses to global change. GCB reviewers probe scale, replication, realism, and causal inference. Guides design choices; it does not collect or simulate data.

ai-agents
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1,052
Gcb SubmissionA

Use when running the final pre-submission preflight for Global Change Biology (GCB) via ScholarOne / Manuscript Central — article-type selection, word/abstract caps, graphical abstract, data availability statement, and required files. Final checks; it does not draft content.

ai-agents
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1,052
Gcb Topic SelectionA

Use when deciding whether a research idea fits Global Change Biology (GCB) and how to frame its significance. GCB wants a mechanistic link between a global-change driver and a biological response, of broad relevance across systems. Tests fit and sharpens the question; it does not generate data or guarantee acceptance.

ai-agents
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1,052
Gcb WorkflowA

Use as the entry point for any Global Change Biology (GCB) manuscript. Routes to the right GCB sub-skill based on where you are in the lifecycle and which article type (Primary Research Article, Technical Advance, Review / Research Review, Opinion / Perspective) fits. It dispatches; it does not draft content.

ai-agentsgo
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Gcb Writing StyleA

Use when drafting or polishing the prose of a Global Change Biology (GCB) manuscript so it reads for a broad ecology / biogeochemistry / Earth-system audience within the journal's length and abstract limits. GCB rewards a clear mechanism, quantified results, and global-change significance. Guides style; it does not ghost-write the science.

ai-agentsgo
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1,052
Gec Conceptual FrameworkA

Use when building the conceptual or analytical framework for a Global Environmental Change (GEC) manuscript. GEC values theoretically rigorous, interdisciplinary work, so the framework must connect concepts (vulnerability, governance, transitions, socio-ecological systems) to the empirical analysis. Builds the framework; it does not run the analysis.

ai-agentsgo
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Gec Data AnalysisA

Use when executing and reporting the analysis for a Global Environmental Change (GEC) manuscript so it survives expert, interdisciplinary review — honest uncertainty, robustness, and triangulation appropriate to quantitative, qualitative, or mixed-methods work. Guides analysis norms; it does not fabricate results.

ai-agentsgo
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1,052
Gec Figures And TablesA

Use when designing the figures, tables, framework diagrams, and maps for a Global Environmental Change (GEC) manuscript, plus the required Highlights. GEC reaches an interdisciplinary, policy-relevant audience, so exhibits must be self-contained and legible across disciplines. Improves exhibits; it does not fabricate data.

ai-agentsgo
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Gec Literature PositioningA

Use when positioning a Global Environmental Change (GEC) manuscript against the relevant literatures. GEC is interdisciplinary, so the paper must engage more than one body of work — environmental social science, governance, the relevant domain literature — and speak across them. Shapes the framing and citations; it does not write the literature review.

ai-agentsgoaws
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Gec Policy Relevance And ImplicationsA

Use when articulating the real-world, policy, and practice implications of a Global Environmental Change (GEC) manuscript. GEC publishes the human and policy dimensions of environmental change, so genuine, evidence-grounded implications are part of the contribution — not a closing sentence. Sharpens the implications; it does not overstate them.

ai-agentsgo
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Gec Research DesignA

Use when defending the research design of a Global Environmental Change (GEC) manuscript — quantitative causal inference, qualitative case work and process tracing, experiments and surveys, or mixed-methods integration. GEC welcomes methodological pluralism but judges each tradition on its own terms. Strengthens the design; it does not write code.

ai-agentsgo
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Gec Review ProcessA

Use to understand how Global Environmental Change (GEC) evaluates a manuscript — double-blind review, editorial screening for scope and social-science fit, the role of multiple external reviewers, and the decision categories. Sets expectations and shapes the paper to survive review; it does not contact editors.

ai-agentsgo
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1,052
Gec Revision And RebuttalA

Use when writing the response to a Global Environmental Change (GEC) revise decision. GEC reviewers are interdisciplinary and often disagree across disciplines, so the response must convert each reviewer on their own terms without alienating the handling editor. Structures the response letter; it does not fabricate new results.

ai-agentsgoapi
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1,052
Gec SubmissionA

Use when running the final pre-submission preflight for Global Environmental Change (GEC) via Editorial Manager — format selection, double-blind anonymization, word and abstract caps, Highlights, the Data Availability Statement, declarations, and ORCID. Final checks; it does not draft content.

ai-agentsgo
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Gec Topic SelectionA

Use when deciding whether an environmental-change project fits Global Environmental Change (GEC) and how to frame it. GEC publishes the human and policy dimensions of global environmental change and requires a significant social-science component, so the test is societal significance and policy relevance, not an environmental result alone. Helps frame the question; it does not collect data.

ai-agentsgo
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1,052
Gec WorkflowA

Use as the entry point for any Global Environmental Change (GEC) manuscript. Routes to the right GEC sub-skill based on where you are in the lifecycle and whether the paper fits a Research Article or a shorter format. GEC is interdisciplinary and social-science-leading; the router's first job is to make sure the human and policy dimensions are front and centre. It dispatches; it does not draft content.

ai-agentsgo
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Gec Writing StyleA

Use when drafting or polishing the prose of a Global Environmental Change (GEC) manuscript so it reads for an interdisciplinary, policy-relevant audience within the word and abstract caps. GEC values clarity and rigor that travel across disciplines. Polishes the writing; it does not draft the analysis.

ai-agentsgo
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1,052
Iclr Artifact EvaluationA

Use when packaging ICLR code, data, checkpoints, demos, logs, and reproduction instructions for reviewers or post-acceptance release, including anonymized links and private discussion-period sharing.

ai-agentsgitapi
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1,052
Iclr Author ResponseA

Use when drafting ICLR OpenReview author discussion replies, revision notes, public comments, restricted comments, and responses to reviewer or AC concerns during the discussion period.

ai-agents
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1,052
Iclr Camera ReadyA

Use when preparing an accepted ICLR paper for camera-ready submission, OpenReview metadata, poster instructions, slide deck, project page, video, and publication logistics.

ai-agents
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1,052
Iclr ExperimentsA

Use when designing or auditing ICLR experiments, including baselines, ablations, scaling laws, robustness, statistics, benchmarks, human evaluation, and compute reporting.

ai-agentsaws
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Iclr Related WorkA

Use when positioning an ICLR paper against prior work, concurrent OpenReview submissions, arXiv papers, benchmark lineages, and adjacent learning-representation claims.

ai-agents
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Iclr ReproducibilityA

Use when strengthening reproducibility for ICLR papers, including seeds, variance, compute, datasets, implementation details, ethics statements, and reviewer-verifiable evidence.

ai-agentsgoapi
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1,052