Designs conjoint and factorial-vignette experiments: attributes and restrictions, effective-N power, estimand choice among AMCE, marginal means, and AMIE, forced choice versus rating, and PAP tiers. Use when planning a conjoint, critiquing an attribute table, sizing respondents and tasks, or testing interactions.
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Turns a theory into falsifiable, pre-registerable hypotheses: DGP and DAG, identification, estimands, SESOIs, test choice among NHST, equivalence, and minimum-effect tests, scope conditions, and hypothesis tiers. Use when converting a research question into testable predictions or predicting a null.
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Audit fielded survey response data for registered elements, data quality, bot and AI-automation screening, and sample integrity, and emit an appendix-ready quality report. Use at soft launch or after fielding, before outcomes are analyzed.
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Design and format publication-quality tables. Use for column order, row grouping, notes, statistical precision, accessibility, and reproducibility.
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Consult an independent, read-only GPT-6 Astra advisor before committing to a substantive interpretation, approach, or final result. Not for routine work, implementation, or file edits. Uses gpt-6-astra at an effort matched to the question.
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Reviews an existing conjoint study for threats to inference and returns severity-ranked findings on design, estimation, measurement error, external validity, and interpretation. Use when checking whether a conjoint design or analysis holds up, or answering referee comments on one.
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Opens a talk, module, paper, chapter, or referee report as a multi-session deliverable. Interviews the author, then scaffolds deliverable.yml, HANDOFF.md, the planning/ wiki, inbox/, and checks/. Use for deadline-driven work spanning sessions.
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Generates 3-5 conceptually distinct approaches (Novel, Surprising, Diverse, Conventional) and holds for selection before implementing. Use before committing to an approach when a task has more than one non-obvious solution; --codex delegates the brainstorm to a fresh subagent.
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Audit a methods section against a 45-item checklist drawn from the APSA Experimental Section rubric, JARS-Quant, CONSORT, and DA-RT. Use before submission or archiving, or to document a pre-analysis-plan deviation.
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Run one consequential, contestable decision through a deliberative committee of GPT-6 Astra and Claude Opus, chaired by fable (default), astra, opus, or sol. Not for factual lookups, brainstorming, routine implementation, independent-coder reliability, or final professional judgment. Use when several options are defensible and the two model families should propose, critique, revise, and cross-rank under a predeclared rubric.
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Run a pre-submission manuscript audit covering argument, numerics, references, writing, figures, methods, preregistration, and replication readiness. Add --codex for a cross-model pass in which Codex and Claude review independently and verify each other's findings.
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Typeset a working paper or journal submission in house-style LaTeX from Markdown, Word, TeX, ODT, RTF, or HTML. Use to convert drafts, build PDFs, or prepare journal-specific spacing, limits, anonymization, disclosures, and citations.
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Writes or reviews a pre-analysis plan before data collection: registry choice (OSF, AEA, AsPredicted, registered reports), locked models and decision rules, code run on simulated data, contingencies, and deviation records. Use when drafting or auditing a pre-registration or PAP, choosing a registry, or handling a deviation.
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Operate or audit a live Qualtrics survey via the v3 APIs without breaking fielding: publish gating, quotas, flow routing, embedded data, panel-vendor redirects, read-back verification, and a read-only pre-fielding audit. Use when publishing or patching a fielding instrument, when a quota counts but never blocks, or before launch.
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Scaffold or audit a social-science replication package, and audit the manuscript and archived research objects against FAIR. Use when setting up or repairing a package, checking one before submission, or drafting data, code, and materials availability statements. Adapted from Yusaku Horiuchi's replication-package-guide.
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Interviews a researcher in rounds (idea, design, or defend stage) until no decision in a research idea, design, or draft is left assumed, recommending an answer to each question and writing settled decisions to a file. Use for 'grill me', stress-testing a design, or an idea not yet a design; --plan for software or process plans.
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Advises on setting up and validating LLM text classification: codebook, learning regime and model choice, prompts, validation against human coding (kappa, F1), hybrid review, measurement error, and reporting, plus a short resumable batch pattern with a rule-based baseline. Use to classify, code, or label text at scale; category discovery goes to topic-modeling.
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Advises on setting up and validating topic models for survey and experimental text: discovery vs. measurement, STM/LDA/BERTopic choice, preprocessing, covariate formulas, choosing K across coherence, FREX, held-out likelihood, and residuals, validating topics against human coding, robustness, and reporting. Coding against a fixed codebook goes to text-classification.
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End-of-session closure. Records what changed into the project's own handoff and log files, separating verified from attempted work, and reports what is uncommitted. Use when wrapping up a session. Twin of sitrep.
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Audits a manuscript's citations for fabricated or nonexistent sources, DOIs that resolve to a different work, mismatches between in-text citations and the reference list, APA 7 or journal style, and whether each source supports the claim it is attached to. Checks entries against Crossref, OpenAlex, and DataCite and labels anything it could not verify NOT CHECKED. Use to check citations, references, a .bib file, or DOIs, or when a source may be AI-invented. Figures and tables go to figure-table-audit.
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Turns a raw Qualtrics conjoint export into an analysis-ready long-format dataset, covering export settings, identifying the implementation, package or manual wide-to-long reshaping, choice-profile alignment, ratings, reference categories, pilot exclusion, and subgroup merges. Use when the user has a conjoint CSV to clean, reshape, or debug, cannot align choices with profiles, or asks what the data must look like before AMCE estimation. Design goes to conjoint-design, validity review to conjoint-diagnostics.
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Designs conjoint and factorial-vignette experiments, covering attribute architecture and randomization restrictions, effective-N power, treatment realism, the choice among AMCE, marginal-mean, and AMIE estimands, forced-choice versus rating designs, and PAP tiers. Use when the user is planning a conjoint, drafting or critiquing an attribute table, asking how many respondents or tasks are needed, whether to report AMCEs or marginal means, or how to test interactions. Reviewing an existing design goes to conjoint-diagnostics, cleaning the export to conjoint-cleaning.
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Reviews an existing conjoint study for threats to inference and returns severity-ranked findings on design integrity, estimation, measurement error, external validity, and interpretation, including the guardrail against reading an AMCE as majority preference. Use when the user asks whether a conjoint design or analysis holds up, has referee comments on a conjoint, or wants a second opinion on estimation or interpretation. New designs go to conjoint-design, reshaping to conjoint-cleaning.
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Designs survey instruments: question wording, scales and index reliability, flow and treatment placement, pretesting, attention and speeding rules, and sensitive questions. Use when writing or revising survey questions, choosing scales, ordering blocks, or planning a pilot.
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