Operate a live Qualtrics survey via the v3 APIs without breaking fielding. Publish gating, quotas, flow routing, embedded data, panel-vendor redirects, and read-back verification.
原文の言語: 英語
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SkillsMP は scdenney/open-science-skills から 84 件の skill を収集しています。skill を開くとソースと詳細を確認できます。
収集済み skill 84 件中 40 件を表示しています。
Operate a live Qualtrics survey via the v3 APIs without breaking fielding. Publish gating, quotas, flow routing, embedded data, panel-vendor redirects, and read-back verification.
原文の言語: 英語
Read or convert any document a research workflow hands you — PDF, Word, PowerPoint, Excel, OpenDocument, RTF, EPUB, or CSV. Use whenever a document has to be read, opened, quoted, summarized, searched, extracted, or added to a source library. Decides whether…
原文の言語: 英語
Operate a live Qualtrics survey via the v3 APIs without breaking fielding. Publish gating, quotas, flow routing, embedded data, panel-vendor redirects, and read-back verification.
原文の言語: 英語
Audit fielded survey response data for registered elements, data quality, bot and AI-automation screening, and sample integrity. Emits an appendix-ready quality report.
原文の言語: 英語
Pre-fielding audit of a live survey over the platform API, with an optional browser walk. Consent-before-anything gates, publish state, force-response completeness, quotas, vendor redirects, anti-bot instrumentation, language-arm symmetry.
原文の言語: 英語
Read or convert any document a research workflow hands you — PDF, Word, PowerPoint, Excel, OpenDocument, RTF, EPUB, or CSV. Fires whenever a document has to be read, opened, quoted, summarized, searched, extracted, or added to a source library, including…
原文の言語: 英語
Scaffold or audit an entire research project repository organized around its source library. Use whenever the user is starting, structuring, organizing, or reviewing a whole project — "set up a research repo", "how should I structure/organize this project",…
原文の言語: 英語
Audit fielded survey response data for registered elements, data quality, bot and AI-automation screening, and sample integrity. Emits an appendix-ready quality report.
原文の言語: 英語
Pre-fielding audit of a live survey over the platform API, with an optional browser walk. Consent-before-anything gates, publish state, force-response completeness, quotas, vendor redirects, anti-bot instrumentation, language-arm symmetry.
原文の言語: 英語
Consult Fable 5 as an independent second reviewer, always at max reasoning effort. The calling session is the main model — Opus 5 or Sonnet 5 — and Fable holds the advisor seat. Use before committing to an interpretation or a substantial piece of…
原文の言語: 英語
Run a multi-model orchestration workflow led by Fable 5, the strongest model on the team. Use when the session is already running on Fable 5 — its sibling opus-orchestrate is the one to use when the session is on Opus 5. The Fable lead does the hard reasoning…
原文の言語: 英語
Run a multi-model orchestration workflow with Claude Opus 5 as the lead, at medium reasoning effort by default. Use when the session is already running on Opus 5 — its sibling fable-orchestrate is the one to use when the session is on Fable 5. The lead is…
原文の言語: 英語
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…
原文の言語: 英語
Spawn full Claude Code peer sessions in their own terminal panes and git worktrees — real sessions, not subagents — each on a directed task with a contract brief, monitored and merged back by the spawning lead. Detects the environment and takes the strongest…
原文の言語: 英語
Run one consequential, contestable decision through a deliberative committee of GPT-5.6 and Claude Opus 5, chaired by opus (default), fable, or sol. Not for factual lookups, brainstorming, routine implementation, independent-coder reliability, or final…
原文の言語: 英語
Scaffold or audit an entire research project repository organized around its source library. Use when starting, structuring, organizing, or reviewing a research repo. Build sources/{og,md,unprocessed}, references.bib, a PDF-to-Markdown converter, a repo-local…
原文の言語: 英語
Design and validate LLM-based text classification. Use for codebooks, prompts, validation samples, agreement statistics, and reporting model-coded data.
原文の言語: 英語
Design VLM-based OCR pipelines. Use for model selection, prompting, architecture, multilingual documents, structured output, and evaluation planning.
原文の言語: 英語
Design and diagnose list experiments (item count technique).
原文の言語: 英語
Fact-check manuscript claims against cited sources in a per-source Markdown knowledge base. Use to audit claim support, overclaiming, direction, scope, and misattribution after source intake is complete.
原文の言語: 英語
Orchestrate complex work as the Codex lead, with a gpt-5.6-sol lead at xhigh effort owning decomposition, integration, and verification while delegating bounded work to cheaper GPT-5.6 tiers and a cross-vendor Claude peer. Not for routine single-context work.…
原文の言語: 英語
Consult an independent, read-only GPT-5.6 advisor before committing to a substantive interpretation, approach, or final result. Not for routine work, implementation, or file edits. Always gpt-5.6-sol at xhigh effort, the flagship tier at its strongest routine…
原文の言語: 英語
Design conjoint experiments covering attributes, power, and AMCE/AMIE estimation. Use for conjoint design choices, attribute tables, estimands, and power planning.
原文の言語: 英語
Diagnose conjoint design integrity, estimation choices, and validity.
原文の言語: 英語
Design cross-national survey experiments covering power, equivalence, and localization. Use for multi-country sampling, measurement comparability, and instrument adaptation.
原文の言語: 英語
Delegate creative divergence to a fresh Codex subagent before implementation. Use when the user explicitly asks Codex to delegate brainstorming, obtain an independent Codex context, or keep implementation separate from approach generation. Generate 3–5…
原文の言語: 英語
Before implementing, generate 3-5 conceptually distinct approaches labeled by creativity dimension (Novel, Surprising, Diverse, Conventional), then hold for selection. Brainstorm-then-select to resist defaulting to the most obvious solution.
原文の言語: 英語
Build falsifiable causal hypotheses. Use for DAGs, FPCI, equivalence testing, mechanism specification, and deriving testable predictions from theory.
原文の言語: 英語
Draft a senior peer-review report on a social-science manuscript.
原文の言語: 英語
Analyze LLM token logprobs and calibration. Use for per-decision confidence, ECE, Brier scores, reliability diagrams, and low-confidence triage.
原文の言語: 英語
Check methods reporting against CONSORT, JARS, DA-RT standards.
原文の言語: 英語
LLM council/panel voting — multi-model coders, consensus rules, inter-rater agreement (kappa, alpha), correlated-error diagnostics.
原文の言語: 英語
Draft or audit scientific introductions. Use for argument logic, framing, contribution structure, and coherence across multiple studies or experiments.
原文の言語: 英語
Run a cross-model adversarial pre-submission audit from Codex. Use when a user explicitly requests the heavier paper-review-lite-codex workflow, independent Codex and Claude review passes, or cross-model verification of a manuscript. Apply the…
原文の言語: 英語
Run a pre-submission manuscript audit covering argument, numerics, references, writing, figures, methods, preregistration, and replication readiness.
原文の言語: 英語
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.
原文の言語: 英語
Clean post-OCR research text. Use for correction, quality assurance, multilingual handling, uncertainty preservation, and provenance-aware cleanup.
原文の言語: 英語
Plan a research project as a durable decision map, resolving one design decision per session until the destination is a defensible, pre-registerable design. Not for executing analyses or writing the paper. Use at the start of a project, when a design has more…
原文の言語: 英語
Compare OCR systems before a bulk run: candidate set, stratified ground truth, CER/WER, normalization, per-language and per-stratum accuracy.
原文の言語: 英語
Runs a deliberative two-model committee — GPT-5.6 Sol and Claude Opus 5 as members, under a selectable chair. Chair defaults to Claude Opus 5; `/model-committee-fable` chairs with Fable 5, and `/model-committee-sol` chairs with GPT-5.6 Sol via Codex, which…
原文の言語: 英語