“usd”的搜索结果

Knowledge base from the OUSD(R&E) guidebook Implementing a MOSA in DoD Programs (Feb 2025). Use for the Modular Open Systems Approach as a DoD acquisition + design discipline: the statutory/regulatory basis (10 U.S.C. 4401–4403, FY2017/FY2021 NDAA, DFARS), the five OUSD(R&E) pillars, the plan→modularize→identify→define→standardize interface lifecycle, technical levers (WBS/MIL-STD-881F taxonomy, standards profiling, API-first software, COTS/cybersecurity), MOSA assessment metrics and tools (PART/OAAT/KOSS/SEAM/MAUT), technology-change and DMSMS management, roadmaps, MOSA across the six AAF pathways, and contracting/IP/data-rights mechanics. SCOPE LIMITS: this is U.S. DoD weapon-system acquisition policy, not a general open-architecture or interface-standards reference — it names standards (FACE, OMS, DISR) without reproducing them, is light on detailed engineering of any specific standard, and does not cover the underlying SE processes (use dau-se-guidebook / nasa-npr-7123) or general systems-engineering theory (use sebok).

中文简介正在准备中。当前显示原文说明。

Autonomer Langlauf-Modus ohne laufende Rückfragen — Startbedingungen (Ziel, Scope, Budgets, Checkpoints), Entscheidungsstufen und Abbruchregeln für unbeaufsichtigte Läufe; erhöht die Ausdauer, nicht die Berechtigung. Nutzen, wenn ausdrücklich ein längerer autonomer Lauf gewünscht ist.

中文简介正在准备中。当前显示原文说明。

ScalarDB Cluster および ScalarDB Analytics のアーキテクチャ、サイジング、構成を見積もるスキル。 性能要件、可用性要件、クラウド環境からScalarDB Cluster Pod数、Kubernetes構成、 バックエンドDB、API Gateway、監視システム等の全体構成を見積もる。 ScalarDB Analyticsを使用する場合はEMR/Databricksのサイジングも含む。 使用タイミング: - 「ScalarDBのサイジングを見積もりたい」「ScalarDB環境を構築したい」 - 「ScalarDB Clusterの構成を決めたい」「ScalarDBの費用を算出したい」 - 「開発/テスト/ステージング/本番環境のScalarDB構成」 - CI/CD、Blue/Green、Canary Deploymentを含む本番環境設計 - 「ScalarDB Analyticsを使いたい」「分析クエリ環境を構築したい」 - 「EMR/Databricksのサイジングを見積もりたい」 出力: Markdown形式の見積もり結果 + HTML形式のレポート 費用: USD/JPY両建て（為替レート明記）

中文简介正在准备中。当前显示原文说明。

Distills enduring architectural decisions and design rationale from wave orchestration plans or historical git changes into structured, tracked Architecture Decision Records (ADRs). Use pre-wave to resolve active architectural constraints or post-wave to record enduring decisions in docs/decisions/.

中文简介正在准备中。当前显示原文说明。

Incrementally studies git history across tagged or pattern-matched intervals (e.g., creation of planning artifacts like EXECUTION_PLAN_N.md, release tags, or milestone commits). Extracts commit diffs, file churn, and subsystem shifts to track feature evolution and architectural convergence, providing structured feeds for ADR distillation.

中文简介正在准备中。当前显示原文说明。

Audit and update an arbitrary codebase to follow the Code.mil federal open-source licensing model (MIT with 17 U.S.C. Section 105 disclaimers and INTENT.md), including CRAN/R package DESCRIPTION setup.

中文简介正在准备中。当前显示原文说明。

Validates code fixes by running the code, checking compilation, verifying runtime behavior, and confirming fixes resolve the reported issue. Use when verifying that bug fixes actually work at runtime.

中文简介正在准备中。当前显示原文说明。

Enforces lean, surgical output. Suppresses conversational fluff and verbose reasoning traces. Use when agent output feels too chatty or repetitive.

中文简介正在准备中。当前显示原文说明。

Plain language directive. Cuts verbosity, corporate jargon, and overused AI vocabulary. Use when you want clear, direct, short writing. No fluff, no hedging, no unnecessary complexity.

中文简介正在准备中。当前显示原文说明。

Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use on ANY coding task: writing, adding, refactoring, fixing, reviewing, or designing code, and choosing libraries or dependencies. Also use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path", or complains about over-engineering, bloat, boilerplate, or unnecessary dependencies. Do NOT use for non-coding requests (general knowledge, prose, translation, summaries, recipes).

中文简介正在准备中。当前显示原文说明。

Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.

中文简介正在准备中。当前显示原文说明。

Guides the discovery, design, validation, and delivery of Agent Skills. Use when identifying skill gaps, creating or revising a SKILL.md, improving skill descriptions, or checking a skill against the Agent Skills specification.

中文简介正在准备中。当前显示原文说明。

Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent.

中文简介正在准备中。当前显示原文说明。

Reads Copilot conversation history and extracts executive-ready success stories. Use when the user asks to study prior Copilot sessions, summarize what was done before, mine evidence, or quantify time, cost, risk, and priority alignment from GitHub Copilot history in any workspace or repository.

中文简介正在准备中。当前显示原文说明。

Performs architectural code reviews focusing on design patterns, duplication, circular dependencies, and refactoring impact. Is the design consistent with the codebase? Use when reviewing code changes for architectural concerns, code smells, or structural issues.

中文简介正在准备中。当前显示原文说明。

Processes JSON on the command line with jq. Use when parsing, filtering, or validating JSON from files or APIs.

中文简介正在准备中。当前显示原文说明。

Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.

中文简介正在准备中。当前显示原文说明。

Create and maintain AGENTS.md files for project onboarding and grounding. Use when initialized in a new project, when project structure changes significantly, or when creating subfolder-level AGENTS.md files for complex monorepos.

中文简介正在准备中。当前显示原文说明。

Design and run reproducible benchmarks. Use when measuring performance scaling, comparing branches, or analyzing speedup metrics.

中文简介正在准备中。当前显示原文说明。

Verifies bug fixes are correct and complete by tracing callers, checking imports/exports, validating path resolution, and confirming no regressions. Does the code work? Use when reviewing code changes for functional correctness.

中文简介正在准备中。当前显示原文说明。

Decomposes a large implementation plan into small-model-sized tasks executed by supervised worker agents in dependency-ordered parallel waves, with a plan-first approval gate inside every task, file-based state for context compaction, and a hard escalation ladder. Use when a master plan or multi-workstream feature is too large for one session and should be executed cheaply by many small agents under frontier-model supervision.

中文简介正在准备中。当前显示原文说明。

GitHub Actions CI/CD setup for Python, R, and multi-platform testing. Use when creating, debugging, or optimizing CI/CD pipelines.

中文简介正在准备中。当前显示原文说明。

Captures web sources and compiles deterministic Markdown reference bundles with metadata and checksums. Use when asked to capture URLs, research web links, bundle search results, or archive web pages into an LLM-ready reference document.

中文简介正在准备中。当前显示原文说明。

Interactive guided walkthrough of code, line by line, where the agent reflects back your explanations without analysis. Use when debugging, reviewing, or understanding code by forced articulation.

中文简介正在准备中。当前显示原文说明。