「orr」の検索結果

Prepare a complete client review meeting prep document for a financial advisor, for whatever timeframe the review covers (quarterly, annual, ad hoc). Given a household name or email and a timeframe, pulls CRM context (Salesforce/Redtail/Wealthbox), portfolio data (Orion/Addepar/Envestnet-Tamarac), estate & tax status (Wealth.com), meeting notes (Zocks or CRM), recent correspondence (Gmail/Outlook), and the household's plan snapshot (MoneyGuide), then assembles a meeting-ready prep doc with agenda, talking points, and action items. Triggers on "pre meeting", "/pre-meeting", "prep for [client]", "quarterly review prep", "get me ready for my meeting with [client]", or "client meeting tomorrow".

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 a .glb or .gltf and make it small, correct, and fast to load in a browser, with a measured before/after report. Use when a model is "too big" or "slow to load", when the user asks to "optimize this GLB", "compress this glTF", or "export for web", or when they mention Draco, meshopt, gltfpack, KTX2, Basis, texture VRAM, draw calls, or a Blender / CAD / photogrammetry / Pascal export headed for Three.js, React Three Fiber (drei useGLTF), Babylon.js, or model-viewer. Covers inspection, spec validation, geometry and texture compression, scene-graph cleanup, and the correctness checks (metres, Y-up, node names, animations, PBR fidelity, alpha modes, vertex colors) that must not regress. Not for editing or modelling geometry, authoring or laying out a scene, generating 3D from text or images, converting from FBX/OBJ/CAD, or debugging a runtime frame rate that has nothing to do with asset size.

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。

Assess the impact of a significant change during sprint execution across the PRD, epics, architecture, and UX documents, and produce a sprint change proposal. Use when the user says "correct course" or "propose sprint change"

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。

Design formative assessments that make students' historical thinking visible — revealing whether they source, close-read, contextualise, and corroborate. Use when assessing historical thinking skills or planning a diagnostic.

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。

Build students' capacity to compare accounts across multiple historical sources — identifying agreements, contradictions, and gaps. Use when students treat individual documents as complete answers rather than partial perspectives.

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 significant changes during sprint execution. Use when the user says "correct course" or "propose sprint change"

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 when the user wants full metadata for a paper — from a DOI, PMID, arXiv id, OpenAlex id, or title. Returns title, author list, first author, corresponding author(s), publication date, journal name + ISO-4 abbreviation, impact factor, volume/issue/pages, DOI/PMID, citation count, and abstract in one record. Triggers on "paper metadata", "who is the corresponding author", "first author of", "what journal / impact factor for this DOI/PMID", "cite this paper", "文献元数据", "通讯作者", "第一作者", "影响因子". PROACTIVELY USE when the user pastes a DOI/PMID/arXiv id or paper title and asks about its authors, venue, or impact.

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。

Reviews Rust code for ownership, borrowing, lifetime, error handling, trait design, unsafe usage, and common mistakes. Use when reviewing .rs files, checking borrow checker issues, error handling patterns, or trait implementations. Covers Rust 2024 edition patterns and modern idioms.

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。

Diagnosis of why structural materials fail — ductile overload, brittle cleavage, fatigue, creep, stress-corrosion cracking, hydrogen embrittlement, and corrosion. Covers Griffith fracture mechanics, the ductile-to-brittle transition, the S-N and Paris fatigue frameworks, fractographic interpretation, and the J.E. Gordon view that strength, stiffness, and toughness are distinct properties that must be understood together to prevent collapse.

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。

Maps the 18 OCapN/CapTP/E-rights patterns reinvented piecemeal across codex-rs to their canonical Spritely/Goblins equivalents and the hermes-* bridge skills that formalize each correspondence. Use when auditing capability architecture in codex-rs, planning a Hoot/Goblins port, or reasoning about which E-rights primitive a codex-rs module implicitly implements.

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。

Test harness for Claude Code skill argument substitution — demonstrates capture-block pre-declaration, XML tag referencing, unintentional variable corruption in code blocks, and correct placement of shell examples in reference files. Use when verifying substitution behavior before applying a pattern to other skills, testing how arguments flow from skill invocations, or understanding the pre-declaration and reference file pattern with greet/farewell/inspect actions.

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。

OCRs scanned or image-only corpora with vision-language models in three phases. Evaluate selects a system by measured CER or WER against stratified human ground truth. Run builds the production pipeline. Clean corrects raw OCR with LLM and rule-based passes, quality diagnostics, and span-level provenance. Use when choosing an OCR model for a corpus, measuring OCR accuracy, transcribing scans at scale, or correcting raw OCR. Born-digital documents with text layers go to doc-to-markdown.

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。

AI agent self-correction mechanisms: error detection, validation loops, recovery strategies, confidence scoring, and iterative refinement

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 when reviewing, debugging, or improving frontend code in this repo (website/ HTML, CSS, JS, service workers, PWA assets) or when asked to "review frontend", "revisa el html/css", "review JS", or "audita el frontend". Reviews for correctness, browser compatibility, accessibility, performance, security (XSS), responsive behavior, and PWA/service-worker correctness, and ends with a "what a user/reviewer would catch" pass.

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。

Validate and improve GitHub Well-Architected Framework (WAF) documentation under the content/ folder for architectural correctness, decision quality, explicit trade-offs, and actionable guidance. Use this when reviewing pull requests, markdown files, or draft content in content/ to ensure recommendations are technically sound, context-aware, and guide readers toward correct architecture and design decisions.

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。

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for DFIR chronology, cross-artifact correlation, persistence chains, and incident timeline reconstruction. Use when the user asks to build a forensic timeline, correlate EVTX, PCAP, registry, disk, memory, mailbox, or browser artifacts, explain the order of attacker actions, or pinpoint the stage where the decisive artifact appears. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。

Decide what to borrow, adapt, or write before building something. Use when the user describes an app, tool, CLI, or feature they want to build and needs to know which parts already exist as open-source GitHub repos (BORROW), which are worth reading and adapting (KITBASH), and which to just write (WRITE). Every repository named is checked against the live GitHub API, so invented ones never reach the user.

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 on any core for first-run planning intake — Phase 0 runs the vendored BMAD-METHOD planning shelf, shared by every core, and Phase 1 (mining `04-prd.md` into intent records plus the Add-ons/sync-and-remote-entities decision) is full-stack-app's and pwa-app's shared procedure — identical mechanics, a different decision at step 5/8. Phase 0 also defines compressed intake, the path a user's explicit "just build it" choice takes on full-stack-app, pwa-app, authored, and copywriting cores: one batched round of questions in place of the shelf, writing a thinned archive at the same paths so Phase 1 (or, on copywriting, that core's own mining step), `ux-planner`, and the Re-entry pass all keep their documented source. Also use for the Re-entry pass, which mines new scope into additional intents without re-running the shelf, on any core with a module axis to add an intent to (full-stack-app, pwa-app, authored) — landing-page has none, so its own new-scope path runs through `hedgehog-landing-loop`'s Correction Protocol instead. Invoked by the `planner` agent, which decides the path; don't run standalone. landing-page runs this skill's Phase 0 on first run, then mines the same archive through `hedgehog-landing-loop`'s own planning-intake section, that core's counterpart to this skill's Phase 1. copywriting runs this skill's Phase 0 the same way (full or compressed), then mines the same archive through `hedgehog-copywriting-loop`'s own planning-intake section into a what/audience/register brief — no module axis, so its own new-scope path runs through that loop's Correction Protocol rather than the Re-entry pass below. An authored core runs this skill's Phase 0, then `hedgehog-core-design`, then this skill's Phase 1 mining against the designed layer sequence. A brownfield adoption (`hedgehog-adopt`) never runs this skill's shelf at all — the drivers BMAD elicits are already settled facts of a repo that already exists.

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。

Verify a competitive programming or LeetCode solution for correctness, edge cases, and performance. Use when asked to "verify my solution", "check my code", "is this solution correct", "test my solution", "review my competitive programming answer", "validate my algorithm", or any solution verification request.

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。

Analyzes securities lending market with borrow cost, short interest dynamics, and fail-to-deliver monitoring. Use when analyzing lending markets, tracking borrow costs, or evaluating short selling dynamics.

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。

Structured debug log analysis for Claude Code sessions — auto-discovers most recent log, runs reducer, extracts error patterns, correlates with full log, produces observability report. Fills 5 identified gaps: hook error body capture, agent identity, file path tracking, stall correlation, success visibility.

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。

Generate publication-ready statistical tables using gt, kableExtra, or flextable. Covers descriptive statistics, regression results, ANOVA tables, correlation matrices, and APA formatting. Use when creating descriptive statistics tables, formatting regression or ANOVA output, building correlation matrices, producing APA-style tables for academic papers, or generating tables for Quarto and R Markdown documents.

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。

Investigate root causes and manage CAPAs (Corrective and Preventive Actions) for compliance deviations. Covers investigation method selection (5-Why, fishbone, fault tree), structured root cause analysis, corrective vs preventive action design, effectiveness verification, and trend analysis. Use when an audit finding requires a CAPA, when a deviation or incident occurs in a validated system, when a regulatory observation needs a formal response, when a data integrity anomaly requires investigation, or when recurring issues suggest a systemic root cause.

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。

Implement AI-powered anomaly detection for operational metrics using time series analysis (Isolation Forest, Prophet, LSTM), alert correlation, and root cause analysis. Reduce alert fatigue by intelligently identifying true anomalies in system metrics, logs, and traces. Use when operations teams are overwhelmed by alert volume, when detecting complex multi-metric anomalies beyond static thresholds, when seasonal patterns make thresholds ineffective, or when needing to predict issues proactively before they impact users.

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。