Analyse existing written feedback for quality, specificity, actionability, and impact on student learning. Use when reviewing teacher or peer feedback to improve feedback practices.
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Analyse existing written feedback for quality, specificity, actionability, and impact on student learning. Use when reviewing teacher or peer feedback to improve feedback practices.
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Analyse a learning task for cognitive load problems and recommend specific design improvements. Use when tasks overwhelm students, instructions feel complex, or materials need simplifying.
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Analyses sales call transcripts (and churn or renewal calls) to find why deals are won, lost, kept or churned. Reads each call across six dimensions (product, messaging, sales process, pricing, competition, customer context), pulls verbatim quotes with the speaker named, counts how often each pattern appears, and writes findings with recommendations. Works with any recorder export or pasted text. Triggers: "win/loss analysis", "why do we lose", "why do we win", "analyse these sales calls", "lost deals", "churn analysis", "objection patterns". Feeds /positioning and /messaging. Not for general meeting summaries or competitor research (use /competitor-research).
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Use whenever the user mentions Betaflight, FPV drone firmware, flight-controller config, PID/filter/rates tuning, or blackbox log analysis — or shares a Betaflight artifact: a CLI diff/dump (lines like 'diff all', 'set ', 'feature ', 'resource ') or a .bbl/.bfl blackbox log, even when not named as such — or runs a chirp tuning session via Sweep Studio / FPVLogForge (a chirp log ID to analyse, 'analyse log', 'résultat chirp', iterative Bode/step/Ms tuning). Covers flight symptoms (oscillations, wobble, propwash, jello, hot motors, drift), motor/ESC and RX/ELRS/CRSF setup, builds from 3" to 10" (cinewhoop, tinywhoop, longrange, X-class), version migrations (4.4 → 4.5 → 4.6), and configuring a new drone from scratch (setup wizard). Trigger even when phrased casually ("mon drone wobble", "PID help", "config FC") — under-triggering is worse than over-triggering.
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Voert de iteratieve desk-review-&-completion-cyclus uit op een regelrecht-corpus — plannen, harvesten/migreren/uitbreiden, multi-agent valideren, bevindingen 4-weg classificeren (modellering-fout / wetgevings-fout / engine-limitatie / acceptabele untranslatable), synthese + heroverweging, documenteren (wetgevings-/stelselfouten-analyse, fixes-plan, engine-limitaties, diagrammen, corpus-status), verifiëren tegen externe bronnen (resolutie-tracker + bronnen-dossier), en een eindrapport per cyclus. Gebruik dit bij corpus-review op correctheid/coverage zonder live expert-sessie, het opstellen van een wetgevings-notitie-bron, schema-migratie, het harvesten van nieuwe wetten, of het aansturen van een autonome completion-loop. Dossier-agnostisch; de regelrecht-methode is de vaste taal. Voor live-validatie met experts: zie regelrecht-audit-products.
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Detects version drift between machine-readable law YAML files and the binding geldende wettekst on wetten.overheid.nl at the YAML's claimed valid_from. Catches the silent failure where authored content lags behind ingevoerde wijzigingen — a YAML dated 2025-01-01 still carrying pre-Stb.-X text. Activate as Step 0 of every regelrecht-stelselanalyse micro-cycle, before any YAML edit. Strict by design: no bypass, no normalization beyond whitespace within a single paragraph; the geldende wettekst is leading and is mirrored verbatim, including errata. Use proactively when starting a stelselanalyse cycle, before harvest/migrate/extend, or when user mentions "drift", "versie", "geldende tekst", or worries that a YAML may be stale relative to wetten.overheid.nl.
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Bouwt de audit- en workshop-producten waarmee juridische experts een machine-leesbare (regelrecht-YAML) vertaling van wet- en regelgeving valideren in een live sessie. Gebruik dit bij het voorbereiden van een expert-workshop of validatie-sessie over een dossier, het maken van een scope-/stelselanalyse, per-artikel audit-checklists, facilitator-materiaal, testcase-scenario's, of sessie-verslagen (intern + extern). Dossier-agnostisch; de regelrecht-methode (YAML, formules, untranslatables, source/override, legal_basis, engine-trace) is de vaste taal. Voor analytische desk-review van een corpus zonder live sessie (wetgevings-/stelselfouten, coverage, multi-agent review): zie de zusterskill regelrecht-stelselanalyse.
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Use this agent when you need to perform custom bioinformatics analyses on genes or proteins that go beyond standard database lookups. This includes situations where existing domain/family annotations from UniProt are insufficient, when you need to verify dubious annotations, or when you need to perform comparative analyses across gene sets. The agent creates reproducible analysis pipelines with proper dependency management and documentation.
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Turn raw customer material into evidence-backed personas and verbatim voice-of-customer language. Two modes - analyse sources the user already has (call transcripts, support tickets, survey responses, sales notes, reviews), or source new material from public places customers actually talk. Produces quoted pains, objections, and switch triggers that other skills consume, never invented ones. Use when the user says "customer research", "voice of customer", "what do our customers actually say", "we need real quotes", "analyse these call transcripts", "read our support tickets", "build a persona from data", "find what customers complain about", or when a persona is marked provisional. For structuring the finished persona into the knowledge base, see brand-context. For the JTBD persona template itself, see customer-persona.
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依据 RGPD 第 28 条、EDPB 07/2020 和 02/2024 号指南、2021 年标准合同条款(CCT)(执行决定 2021/914)、EDPB 01/2020 号建议(Schrems II 之后的补充措施)以及《欧盟条例 (UE) 2024/1689》(《人工智能条例》),对数据处理协议(DPA)进行系统性分析。生成逐条款的 结构化报告(18 个条款:13 项强制 + 5 项补充),附 🟢/🟡/🔴 诊断、可直接插入的 救济条款、国际传输的详细分析、《人工智能条例》核验以及应向供应商提出的问题。 触发词:"analyse de DPA"、"audit DPA"、"vérifier un DPA"、"DPA fournisseur"、 "data processing agreement"、"art. 28 RGPD"、"sous-traitant RGPD"、"négociation DPA"、 "review DPA"、"conformité contrat sous-traitance"。
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Conception pipeline for Codex. Equivalent to the repository's Claude skill: detect epic/task/bug mode, then delegate to the existing repo agents and workflows. Usage: /analyse [<issue#>] [<description>]
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Conception pipeline. Détecte le mode (epic/task/bug) selon le type d'issue ou le prompt et invoque les agents appropriés. Usage: /analyse [<issue#>] [<description>]
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Fableクラスの思考プロセスを任意のモデルで再現する思考スキャフォールド。問いの再構築、 前提の検証、選択肢空間の展開、反証、確信度つきの収束という順序をフェーズとゲートで強制する。 設計判断・技術選定・調査・分析・提案など、結論を間違えるコストが高い非自明なタスクで使用。 「深く考えて」「幅広い視野で」「多角的に検討して」「Fableのように考えて」がトリガー。 Use when asked to think deeply, consider all angles, or for high-stakes decisions and analyses.
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Analyse experiment results, run validity checks (SRM, exposure parity, data integrity, novelty/primacy), interpret causally, make a ship/iterate/kill decision against the pre-declared rule, and append to cumulative learnings. Forces honest readouts — strips significance claims from underpowered or peek-violating tests; never lets directional results masquerade as causal wins. Load when results exist, or when the user says "read out this experiment", "analyse the test", "did the test win", "interpret the results", "what did we learn", "ship or kill", or when the experimentation orchestrator routes here.
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Analyse rhétorique et épistémologique d'articles, discours et textes argumentatifs. Utiliser ce skill quand l'utilisateur demande d'analyser la qualité argumentative d'un texte, d'identifier des sophismes ou biais, d'évaluer la fiabilité des sources citées, de déconstruire la logique d'un raisonnement, ou de produire une réécriture critique structurée d'un document.
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기존 저장소의 파일 구조, 의존 관계, 컴포넌트와 라우팅을 기록합니다. 에이전트가 마이그레이션이나 수정 작업에서 반복해서 참조할 구조 데이터를 만듭니다.
Review stock analysis, technical backtests that simulate strategies on historical data, and saved research for selected tickers. Examine research dates, model details, risk factors, and simulation limits when reviewing a stock or watchlist.
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Classify market conditions as bullish, bearish, ranging, or volatile to guide strategy selection and historical testing. Distinguish synthetic demonstrations from analysis of actual price data, with confidence levels and historical comparisons where available.
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Find Danish jobs for graduates and highly educated candidates through Akademikernes Jobbank. Filter by industry, education, region, or remote work, then retrieve posting details for graduate trainee, Ph.d., postdoc, and other roles.
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Plan study sample sizes, estimate statistical power—the chance of detecting an assumed effect—and find the smallest detectable effect. Supports standard tests and simulations for complex designs, with sensitivity analyses and sample size justifications.
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Explore gene, drug, disease, and phenotype associations in a downloaded PrimeKG CSV. Retrieve direct relationships, disease summaries, and paths through one intermediate node while preserving relationship types and data provenance for reproducible research and hypothesis generation.
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Process mass spectrometry data using scripts for format conversion, signal cleanup, peak detection, and quantification across samples. Prepare protein and metabolite analyses with identification filtering, candidate annotations, data tables, and plots.
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Combine laboratory animal welfare measurements into reference-relative RELSA severity scores. Analyze individual trajectories, explore forecasts for specified observation times, and derive candidate score zones, with explicit checks on normalization, reference selection, prediction intervals, and evaluation limits.
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Analyze DepMap cancer model data to rank genes required for cell survival, compare groups defined by biological markers, and explore drug responses. Release tracking and statistical checks help organize evidence for research hypotheses.
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