「core」の検索結果

OWASP Top 10 for LLM Applications (2025) knowledge base for identifying, assessing, and remediating large language model security risks.

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。

Create or resume an evidence-based RPI implementation plan with an optional independent critique. Use when a task needs an implementation plan or an existing plan needs revision.

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。

Consolidated accessibility skill entrypoint for WCAG 2.2, ARIA Authoring Practices, cognitive accessibility, Section 508, EN 301 549, design intent verification, and the Accessibility Planner workflow.

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, load, and reliability (SLO/SRE) planning for production readiness. Use when defining service level objectives, load characterization, capacity, latency budgets, stress/soak/spike test plans, false-positive baselines, and reliability targets. USE FOR: SLO/SLA definition, load testing plan, performance budget, capacity planning, reliability/SRE backlog, latency targets, error-budget policy. DO NOT USE FOR: executing load tests (use Azure Load Testing tooling), security threat modeling, RAI assessment, privacy/compliance planning, or authoring/restating PRD requirements (cite the PRD's existing NFR/FR ids instead).

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。

Authors Vally conformance tests for prompts, instructions, agents, and skills, and refuses jailbreak, prompt-injection, harmful-elicitation, TOS, CoC, and PII-extraction stimuli

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。

Foundational Python best practices, idioms, and code quality fundamentals

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。

Capture VS Code screenshots and self-contained browser animation scenes through Playwright. Use for editor evidence, slide imagery, or silent WebM scene clips.

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。

Shared backlog conventions for Azure DevOps, GitHub, and Jira. Use for platform resolution, autonomy tiers, sanitization guards, and story quality, and for Azure DevOps pull request creation and build status or log retrieval.

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。

Read-only backlog planning for Azure DevOps, GitHub, and Jira. Use to discover, triage, sprint-plan, or resume without mutating a tracker.

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。

Experiment design reference for problem-class framing, Minimum Viable Experiment coaching, hypothesis formation, vetting and red flags, and experiment readiness. Use when translating a stated business outcome into candidate data-science problem classes, or when framing, vetting, scoping, or evaluating an experiment of any kind, including data feasibility, architecture, LLM, performance, use-case, UX, prototyping, and hardware experiments.

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。

Create, improve, refactor, replace, review, or validate prompts, instructions, agents, subagents, and skills. Use for Copilot customization cleanup, extending HVE workflows with project-specific capabilities, and parent-owned correction of material review findings.

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。

Authoring skill for Architecture Decision Records (ADRs) supporting capture, from-planner-handoff, and adopt-template entry modes with selectable Y-Statement or MADR v4.0.0 output templates, supersession lineage, and ASR trigger evaluation.

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。

Assemble ordered frames or clips with narration and optional synchronized scene transitions into an MP4 via FFmpeg

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。

Review code changes from multiple perspectives with context bootstrap, depth-tier rigor, and structured findings output.

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。

State, resume, reconstruction, job-lifecycle, transition, and flow-state mechanics for the Data Science and Engineering Coach. Loaded by the coach; not a user entry point.

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 Thinking handoff knowledge for research-ready rpi-research inputs and DT-aware rpi-plan, rpi-implement, and rpi-review context

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。

Create or assess an evidence-grounded, falsifiable outcome hypothesis: a testable prediction of what measurable business result will change, for whom, by when, and how leading and lagging indicators will prove or disprove it. Use when framing measurable outcomes, turning an MVP, POC, feature, or technical initiative into a beneficiary result, defining targets and indicators, or judging whether evidence is strong enough to invest. Also applies to business outcome hypotheses, value hypotheses, and outcome statements.

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 GitLab merge requests and pipelines with a Python CLI

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。

Author and validate durable data and ML feasibility studies using the Feasibility Study Interchange Profile, constrained YAML authority, UUID URN identity, lifecycle lineage, and evidence traceability. Use when assessing whether available data and technical evidence support a proposed outcome.

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。

Mutating backlog execution for Azure DevOps, GitHub, and Jira. Use to create one item or apply a reviewed handoff to a confirmed tracker.

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。

Coach a UX practitioner through problem framing, running a design critique, or making an evidence-backed case to a skeptical stakeholder. Use when the practitioner has a live UX task and wants to think it through rather than receive an answer.

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 customer-card PowerPoint content YAML from Design Thinking canonical artifacts and build using the shared PowerPoint skill pipeline

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 evaluation datasets and supporting documentation for AI systems and agents, covering the scoping interview, difficulty distribution, dataset contract, sample review, and metric and tooling selection. Use when building or reviewing an evaluation set for a conversational agent, assistant, or retrieval-grounded AI system.

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。

Video-to-GIF conversion with FFmpeg two-pass optimization

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。