Unified dashboard panel pattern combining circuit breaker resilience with enhanced UI features like retry logic, state persistence, and detailed error handling.
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概要と使いどころ
Unified dashboard panel pattern combining circuit breaker resilience with enhanced UI features like retry logic, state persistence, and detailed error handling.
日本語の概要は準備中です。原文の説明を表示しています。
Multi-layer workflow for creating complete panel features by analyzing existing patterns and generating coordinated server routes, services, UI components, registration, styling files, AND explicitly wiring new handlers into the server's dispatch table (supports both Express middleware and manual http.createServer switch/case patterns).
日本語の概要は準備中です。原文の説明を表示しています。
Multi-layer workflow for creating complete panel features by analyzing existing patterns and generating coordinated server routes, services, UI components, registration, and styling files.
日本語の概要は準備中です。原文の説明を表示しています。
Manage Mixpanel Headless authentication: check session state, list/add/use accounts, run OAuth login, switch projects/workspaces, manage targets, and check bridge credentials.
日本語の概要は準備中です。原文の説明を表示しています。
Run or plan tumor-normal, tumor-only, WGS, WES, or cancer-panel somatic variant workflows with pairing, contamination, panel-of-normals, purity, QC, and annotation checks.
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Use this skill alongside figma-use when the task involves translating an application page, view, or multi-section layout into Figma. Triggers: 'write to Figma', 'create in Figma from code', 'push page to Figma', 'take this app/page and build it in Figma', 'create a screen', 'build a landing page in Figma', 'update the Figma screen to match code', 'convert this modal/dialog/drawer/panel to Figma'. This is the preferred workflow skill whenever the user wants to build or update a full page, modal, dialog, drawer, sidebar, panel, or any composed multi-section view in Figma from code or a description. Discovers design system components, variables, and styles from Code Connect files, existing screens, and library search, then imports them and assembles views incrementally section-by-section using design system tokens instead of hardcoded values.
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Use when a question, decision, plan, tradeoff, or claim needs a rigorous verdict and one perspective is not enough. Spawns a panel of 3 to 5 subagent jurors that form independent blind opinions, deliberate anonymously under an anti-anchoring and anti-sycophancy protocol, and return one committed verdict with confidence, preserved dissent, and a concrete next action. Domain-agnostic across engineering, architecture, data, product, hiring, strategy, vendor choice, build-vs-buy, and research design. Trigger phrases include "convene a jury", "have agents debate and decide", "get a panel to decide", "multi-agent decision", "stress-test this and decide", "monte um juri", "tribunal de agentes", "painel para decidir". Do NOT use to only critique without deciding (use the-fool for that), to build a plan or write the solution itself, or for simple factual lookups.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill alongside figma-use when the task involves translating an application page, view, or multi-section layout into Figma. Triggers: 'write to Figma', 'create in Figma from code', 'push page to Figma', 'take this app/page and build it in Figma', 'create a screen', 'build a landing page in Figma', 'update the Figma screen to match code', 'convert this modal/dialog/drawer/panel to Figma'. This is the preferred workflow skill whenever the user wants to build or update a full page, modal, dialog, drawer, sidebar, panel, or any composed multi-section view in Figma from code or a description. Discovers design system components, variables, and styles from Code Connect files, existing screens, and library search, then imports them and assembles views incrementally section-by-section using design system tokens instead of hardcoded values.
日本語の概要は準備中です。原文の説明を表示しています。
Electric split with hand-drawn script — offset panels slide in, display title rises with an outlined word, script strokes itself in.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill whenever the user wants to conduct an event study, create event study plots, test for parallel trends, implement difference-in-differences designs, or work with any panel data estimation that involves pre/post treatment comparisons. Trigger on phrases like "event study", "parallel trends", "pre-trends", "dynamic treatment effects", "leads and lags", "TWFE", "two-way fixed effects", "staggered adoption", "staggered treatment", "difference-in-differences", "DiD", "Sun and Abraham", "Callaway and Sant'Anna", "de Chaisemartin", "Borusyak", "did_multiplegt", "fixest", "did2s", "bacon decomposition", or any reference to plotting coefficients around a treatment event. Also trigger when the user uploads panel data and wants to estimate treatment effects with variation in treatment timing. All code is in R.
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Use this skill to run a multi-persona expert advisory review on a labelled pull request in microsoft/apm. panel-mode (full | lean | delta) selects a surface-gated roster plus a CEO synthesizer; omitted or unknown mode is lean. Do not spawn inactive stubs. The orchestrator is the sole writer to the PR: ONE recommendation comment, no verdict labels, no merge gating. The panel is advisory -- it surfaces findings, prioritizes follow-ups, and renders a ship-recommendation that the maintainer and author weigh.
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Use this skill to translate a classifier's in-place verdict into a precise, page-by-page work plan for the docs-sync panel. Activate after docs-impact-classifier returns verdict in_place; reads the candidate page list, fetches the actual page contents, narrows scope to specific sections within each page, and emits the per-page task brief the panel fans out against.
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Automate Mixpanel tasks via Rube MCP (Composio): events, segmentation, funnels, cohorts, user profiles, JQL queries. Always search tools first for current schemas.
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Two stages: first a single-page sheet of numbered panels from an image model, then that sheet fed to Seedance as the reference. The sheet owns order, framing and timing, and the video prompt only has to connect the panels. Use when the user wants a Seedance 2.5 / 2.0 video prompt for this kind of clip (Storyboard grid to video; 中文触发词: 分镜网格转视频, 分镜图, 九宫格, 故事板), or asks how published cases of this type were prompted. Read references/cases.md before drafting.
日本語の概要は準備中です。原文の説明を表示しています。
Treats a ctDNA assay as a molecule-counting experiment at the Poisson edge and builds its analytical-validation case the measurement-science way. Covers the genome-equivalent currency (~330 haploid copies/ng), the lambda = input_GE x VAF sampling ceiling (lambda>=3 for ~95% detection), the error-suppression ladder (raw NGS ~1e-3 -> single-strand UMI ~1e-4/1e-5 -> duplex <1e-7), the CLSI EP17 LoB/LoD/LoD95/LoQ framework, the per-locus-vs-panel-integrated LoD distinction that lets bespoke MRD reach ppm, contrived/SEQC2 reference standards, and honest LoD reporting conditioned on input mass + consensus depth + replicate detection rate. Use when stating or trusting a sensitivity claim, designing a dilution-series validation, deciding how many genome equivalents are needed at a target VAF, choosing a single-locus vs panel-integrated LoD, or auditing a "detects 0.1% VAF" claim.
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Detects somatic mutations in circulating tumor DNA, treating low-VAF detection as a signal-versus-noise problem set by error suppression and molecules sampled, not by the choice of caller. Distinguishes de novo CALLING (scanning a panel for unknown variants, bounded by per-locus error and multiple testing) from tumor-informed DETECTION (tracking a pre-specified variant set, where panel integration reaches single-ppm). Covers VarDict and Mutect2 for de novo calling, UMI-aware callers, and a pysam-based known-variant VAF tracker, with matched-WBC subtraction as the mandatory defense against clonal hematopoiesis (the dominant false positive). Use when calling or tracking tumor mutations from plasma cfDNA, setting a VAF threshold, or deciding whether a low-VAF call is tumor versus CHIP.
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Estimates tumor fraction (the genome-wide proportion of cfDNA molecules that are tumor-derived, the cfDNA analogue of bulk-tumor purity) from shallow whole-genome sequencing with ichorCNA, an HMM over 1 Mb bins that jointly EM-estimates tumor fraction, ploidy, and subclonal prevalence over a normal/ploidy grid. Encodes the load-bearing reframes: tumor fraction is the quantity that travels across assays and is NOT mutation VAF (clonal-het VAF approximately TF/2), CNA-based estimation has a hard ~3 percent limit-of-detection floor, and near-diploid or copy-neutral-LOH genomes return a falsely low value. Selects the estimator by data type (sWGS to ichorCNA, deep panel to max-VAF, methylation to deconvolution, sub-3 percent to fragmentomics or methylation). Use when quantifying tumor burden from a liquid biopsy, picking a tumor-fraction estimator for a given assay, or reconciling a TF estimate against a panel VAF.
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Calls microsatellite instability from WES/WGS/targeted-panel with MSIsensor, MSIsensor-pro, MSIsensor-ct (panel-aware), mSINGS, and MANTIS for FDA pembrolizumab MSI-H pan-tumor / Lynch syndrome / dMMR ICI biomarker. Use when stratifying ICI eligibility (Le 2015), pairing MSI with TMB-H (Sha 2020 / Salem 2018), screening Lynch syndrome (universal IHC + MSI), or distinguishing MSI-H tumors from POLE-exo hypermutator with overlapping signatures.
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Use when modeling hard surface in ZBrush 2026 (sci-fi helmet, weapon, prop, armor plates, mechanical parts, kitbash, vents, panel lines, bolts, concept to game asset), when using ZModeler, Dynamic Subdivision and creasing, Live Boolean, Knife, Clip, Slice or Trim curves, IMM, ArrayMesh, NanoMesh or Panel Loops, or when edges look razor sharp, a Make Boolean Mesh fails or leaves holes, planes look wobbly, Mirror And Weld erased an edit, or ZRemesher ruins a hard-surface part.
日本語の概要は準備中です。原文の説明を表示しています。
Convert comic book panels, manga pages, webtoons, and illustrated storyboards into animated video using Seedance 2.0 on Higgsfield. Use whenever the user wants to animate comics, bring illustrations to life, convert manga to video, animate storyboards, or create motion from static sequential art. Triggers on: comic to video, manga animation, panel animation, storyboard to video, webtoon animation, comic book motion, sequential art, graphic novel animation, or any illustrate-to-animate request. Use even when user says "make this drawing move" or "animate this page.
日本語の概要は準備中です。原文の説明を表示しています。
How to read experiment results without fooling yourself. Confidence intervals, p-values, multiple testing, sequential testing, CUPED, heterogeneous treatment effects, ratio metrics, network effects, dashboard reconciliation, and the interpretation failures that produce confidently wrong shipping decisions. Use this skill whenever the user is reading a finished experiment result panel and about to make a ship, kill, or iterate decision, or when an experiment number does not match the dashboard number. Triggers on read experiment results, result panel, ship or kill decision, p-value, confidence interval, statistical significance, multiple testing, peeking, sequential testing, CUPED, variance reduction, heterogeneous treatment effects, ratio metric, network effects, inconclusive test, experiment versus dashboard mismatch. Use `experiment-design` instead when the test has not run yet and the question is hypothesis, sample size, duration, or what to test.
日本語の概要は準備中です。原文の説明を表示しています。
Audit brand entity facts AI engines trust: Wikidata, Knowledge Panel. "is our Knowledge Panel accurate"
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Verification-first methodology for the Special Panels for Serious Crimes of the Dili District Court (UNTAET, 2000–2006). Citations are verified against JSMP, the UN archives and legal-tools.org. Covers the Los Palos case, the Serious Crimes Unit caseload (391 indicted; about 88 tried) and the SPSC-vs-Jakarta distinction. Research aid, not legal advice. Part of the open-source "Skills for International Justice" library — methodology: github.com/jeannesulzer/international-criminal-tribunals-skills
日本語の概要は準備中です。原文の説明を表示しています。
Performance scorecard design, post-matter feedback collection, QBR preparation, and firm comparison for in-house legal ops teams evaluating outside counsel. Design a scorecard framework calibrated to your team's maturity level. Produce post-matter feedback forms for supervising attorneys to complete at matter close. Prepare a QBR pack with agenda, data summary, and talking points for structured business reviews. Produce a side-by-side firm comparison for panel decision-making. Trigger on: 'design a performance scorecard', 'how do we evaluate our firms', 'build us a scorecard', 'post-matter feedback form', 'feedback at matter close', 'collect feedback on the firm', 'QBR', 'quarterly business review', 'prep for the firm review', 'what should I raise with the partner', 'compare the firms', 'which firm is performing better', 'rank our panel', 'firm performance data', 'scorecard framework', 'evaluate outside counsel', 'annual firm review', 'how are our firms performing'.
日本語の概要は準備中です。原文の説明を表示しています。