「analyse」の検索結果

Knowledge base from the NASA Cost Estimating Handbook (CEH) v4.0. Use for NASA's 12-step, three-part cost estimating process (Project Definition, Cost Methodology, Cost Estimate); the WBS, CADRe, and ONCE data backbone; estimating methodologies (analogy, parametric/CER, engineering build-up, EVM, Delphi); ground rules and assumptions, data normalization and inflation (BY/CY/RY); the point-estimate-to-S-curve cost-risk chain and Unallocated Future Expense (UFE) reserves; Joint Cost and Schedule Confidence Level (JCL) analysis via probabilistic cost-loaded schedules; decision-support analyses (sensitivity, trade studies, make/lease-vs-buy, affordability, CAIV); and economic analysis (discounting, NPV, OMB Circular A-94). The cost-estimating complement to NASA's SE and risk packs. Does NOT reproduce the handbook's tool-specific procedures, worked examples, or appendix-depth methods (it names the appendices), nor cover full DoD/GAO cost guides, schedule construction, or formal risk management beyond the cost interface.

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Neutrale moralisch-rechtliche Prüfinstanz für Politik und Entscheidungen — der lauffähige Prototyp des Forschungsprojekts "Die Position der Ungeborenen" (Schattenmodus Stufe 1). Nutze diesen Skill, wann immer eine politische Entscheidung, ein Gesetz(entwurf), eine Reform, ein Haushaltsbeschluss oder eine gesellschaftliche Streitfrage analysiert, geprüft oder begutachtet werden soll — auch bei Formulierungen wie "prüfe aus Sicht künftiger Generationen", "Gesetzespass", "was sagt das Grundgesetz dazu", "Superposition-Prüfung", "Gesetzesgeschichte/Containeranalyse", "Folgenabschätzung", "analysiere diese Reform", "lebende Verfassung" oder wenn der User eine Politik-Fragestellung mit Bitte um neutrale, mehrstufige Bewertung einbringt. Orchestriert die 5-CORE-Architektur (config.json): moralische Superposition-Instanz, Gesetzbuch-Verkörperungen, zweistufige Folgenabschätzung (retrospektiv/prospektiv mit Evidenzhierarchie), Wissens-Handler mit lokalem Speicher, einstellbarer Workflow.

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Meta-skill: Structured thinking as a 3-phase workflow. Combines analysis (think), ideation (brainstorm), and decision-making (decide) into one continuous process.

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Dieser Skill sollte genutzt werden, wenn der User private oder halbformale E-Mails schreiben, beantworten, absagen, nachfassen, kürzen, umformulieren oder im eigenen Stil entwerfen lassen will, besonders bei Terminen, offiziellen Absagen, freundlichen Kurzantworten und kontaktabhängigem Ton. Profilanalyse erst bei einem konkreten Mail-Schreibauftrag starten.

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Prüfungsvorbereitung, Selbsttests, Probeklausuren und systematische Fehleranalyse.

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Prepares the trend update for a recurring emailed report: identifies report emails not yet processed, extracts the configured metrics from their spreadsheet, CSV or PDF attachments, returns new rows for an append-only trends sheet and writes a DRAFT summary with period-on-period deltas and flagged anomalies. Use when the user asks to "update the trends for the weekly report", "analyse the latest monthly report", "what changed in the latest report", "do the latest numbers look unusual" or "set up tracking for a report that arrives by email". Do not use for a single file with no trend state, use dataset-insight-pack instead. Drafts for human review; never approves, authorises or signs off.

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Synthesises training survey responses and manager notes into a DRAFT training needs report by role: coded needs with record counts per role (n of N), the evidence type behind each count, anonymised quotes cited to record codes, disagreements between what staff report and what managers observe, gaps where a role is under-represented or a required skill has no evidence, and follow-up questions to settle before any course is designed. Never rates an individual, ranks a team or turns a count into a competence verdict. Use when the user asks to "analyse this training survey", "what training do our teams need", "summarise the manager feedback on skills gaps", "build a training needs analysis by role" or "which roles have the biggest skill gaps". Do not use for turning an agreed need into a course, use course-outline-builder instead; for exit interviews, use exit-interview-synthesis. Drafts for human review; never approves, authorises or signs off.

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Synthesises exit interview notes or leaver survey responses into a DRAFT themed report: coded themes with record counts and shares, anonymised verbatim evidence, breakdowns by broad group only for groups that meet a minimum group size, referred items and open questions for the people team, without naming or identifying any individual. Use when the user asks to analyse, summarise, code, theme or report on exit interviews, leaver feedback, attrition interviews or departure surveys, or says "what are our leavers telling us", "theme these exit interviews" or "summarise the leaver survey". Do not use for customer or product feedback, use customer-feedback-theme-synthesis instead; for redacting one document with no theming, use document-deidentification-pass. Drafts for human review; never approves, authorises or signs off.

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Builds a DRAFT quiz from the training content the user supplies (slide deck, manual, e-learning script, session transcript, procedure): numbered questions with the correct answer, distractors drawn from the content itself, an explanation quoting the source passage with its location, a difficulty tag (Recall, Apply, Analyse) with its basis, and a coverage table showing which sections and objectives each question tests and which are left uncovered. Use when the user asks to "build a quiz from this deck", "write knowledge check questions for this module", "create an assessment from this training", "test understanding of this procedure" or "which sections does this quiz cover". Do not use for a reader-facing question and answer page built from documents, use faq-builder instead; for writing the procedure itself from notes or a walkthrough, use sop-drafter. Drafts for human review; never approves, authorises or signs off.

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Reads one spreadsheet, CSV export or pasted table together with the user's question and drafts an insight pack: a data profile, observations cited to named columns and values and framed as leads, caveats, and suggested charts and follow-up analyses. Every figure carries the label "as read, verify in source"; correlation is never stated as causation. Use when the user asks to "profile this spreadsheet", "what does this data say", "find anomalies in this extract", "give me a first read on this CSV" or "summarise this table". Do not use for a purchase order log or spend extract, use purchase-order-anomaly-review instead; for actuals versus budget, use budget-variance-explainer instead; for a report that arrives by email on a schedule, use report-attachment-analyzer instead. Drafts for human review; never approves, authorises or signs off.

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Synthesises a batch of customer feedback (survey answers, reviews, ticket and chat comments) into a DRAFT themed report: coded themes with record counts and shares, anonymised verbatim quotes cited to record codes, contradictions and unverified claims, and the follow-up questions to answer next. Produces no sentiment score or percentage positive as fact; ratings appear only as distributions with n. Use when the user asks to "theme this feedback", "what are customers saying", "summarise these survey answers", "analyse these reviews", "find the top complaints in these comments" or "code this voice of the customer data". Do not use for exit interviews, use exit-interview-synthesis instead; for sorting a live queue and drafting replies, use ticket-triage-pack; for project retrospectives, use lessons-learned-synthesis. Drafts for human review; never approves, authorises or signs off.

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Apply to any non-trivial work, not just bulk work: edits, migrations, analyses, checks. Build the tool that does it or proves it (codemod, script, generator, or a skill your subagents follow) instead of working by hand. The tool is the artifact a reviewer can rerun.

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Data Analyst IA — Expert en analyse de données (SQL, BI dashboards, Metabase, Superset, reporting, KPIs)

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Expert en optimisation du taux de conversion (A/B testing, heatmaps, analyse funnel, persuasion)

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Expert en stratégie de marque (positionnement, messaging, architecture de marque, analyse concurrentielle)

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Expert en analyse du churn (cohort analysis, survival curves, predictive models, at-risk signals)

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Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

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Prepares statistical reports for clinical trials following CONSORT 2025, SPIRIT 2025, ICH E9(R1) estimands, and FDA 2023 covariate adjustment guidance. Covers Table 1 generation, analysis populations (ITT/FAS/PP/Safety), the 5 ICH E9(R1) intercurrent-event strategies, MMRM under MAR (mmrm), reference-based MI (rbmi J2R/CR/CIR), Permutt tipping-point sensitivity, and Rubin's-rules vs frequentist variance debate. Use when preparing regulatory submissions, defining estimands, or implementing missing-data sensitivity analyses.

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Designs adaptive clinical trials including group-sequential (O'Brien-Fleming, Pocock, Lan-DeMets spending), sample-size re-estimation (blinded Friede-Kieser, unblinded Cui-Hung-Wang, Mehta-Pocock promising zone), seamless Phase 2/3 with treatment-arm selection, population enrichment, and response-adaptive randomisation. Covers FDA 2019 Final Adaptive Designs Guidance, FDA 2022 Master Protocols, and ICH E20 Step 2b/3 draft (June 2025, NOT final). Use when planning interim analyses, sample-size re-estimation, or master/platform-trial designs.

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Plan and execute reproducible computational research with explicit inputs, environments, provenance, deterministic steps, validation, and workspace outputs. Use for analyses that must be rerun, audited, or handed to another researcher.

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End-to-end observational epidemiology analysis — from research question (PECO Population/Exposure/Comparator/Outcome) to publication-ready statistical report. Covers cohort/case-control/cross-sectional design, regression with confounders, propensity scoring, sensitivity analysis. Writes Python code for every step. Use for epidemiology study analysis, NHANES/UK-Biobank-style analyses.

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Designs Bayesian clinical trials including Phase I dose-finding (BOIN, CRM, EWOC, mTPI-2), meta-analytic-predictive (MAP) priors with robust mixtures for external data borrowing, EXNEX for basket trials, hierarchical models for safety AE (Berry-Berry), Bayesian platform trials (I-SPY 2, GBM AGILE, REMAP-CAP), and posterior probability stopping rules. Covers FDA Bayesian Devices Guidance (2010), FDA Bayesian Methodology in Drugs Draft (January 2026), BOIN Fit-for-Purpose qualification (December 2021), and Project Optimus dose-optimisation. Use when designing dose-finding studies, platform trials, or sensitivity analyses with informative priors.

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Performs subgroup and heterogeneous treatment effect (HTE) analyses for clinical trials. Covers Mantel-Haenszel pooling, Breslow-Day, interaction tests in regression, RERI for additive interaction, modern data-adaptive HTE methods (STEPP, SIDES, causal forests, X/R-learners), Bayesian shrinkage (Dixon-Simon, MAP, EXNEX), graphical multiplicity (Bretz-Maurer), and credibility frameworks (Sun BMJ, EMA 2019). Use when analyzing treatment effects across patient subgroups for regulatory submissions or precision-medicine claims.

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Implements missing-data sensitivity analyses for confirmatory clinical trials including MMRM under MAR (with Kenward-Roger correction), reference-based multiple imputation (J2R, CR, CIR, LMCF per Carpenter-Roger 2013), Permutt delta-adjustment / tipping-point analysis, pattern-mixture identifying restrictions (CCMV, NCMV, ACMV), and the Cro vs Bartlett variance debate. Use when handling missing primary or secondary endpoint data in regulatory submissions following NRC 2010 and ICH E9(R1).

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