533 件 ・ 関連度順
概要と使いどころ
Shape every agent comment as a short typed brief the owner can triage in seconds — 🔴 issue · 💡 proposal · ✅ done · 🔀 choice · 🛠 action · 👀 review — with all the depth collapsed behind it. Enforced by the require-owner-brief hook. Use before posting ANY GitHub comment as an agent, or when asked to "make this shorter", "brief me", "just tell me what I need to do".
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。
Recreate the nuxt-crouton dev environment from scratch and survive its install/build traps — the pnpm toolchain, the cold-start sequence (why packages must build before apps prepare), the version catalog and workaround pins, the per-app typecheck rule, required env vars, and the known environment traps. Use when setting up a fresh clone/worktree, when "pnpm install" or "nuxt prepare" fails, when an app won't boot after install, when typecheck output looks insane, or when a tool "isn't available". Trigger phrases: "set up the repo from scratch", "why does typecheck show thousands of errors", "playwright install fails", "what pnpm/node version". (Exact error strings — "Could not load '@fyit/crouton'", "Cannot find module '@vue/compiler-sfc'" — route via crouton-diagnostics-index first; it points back here for depth.)
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。
Front-end conventions review for Vue surfaces — the component-usage analog of /a11y, pointed at Nuxt UI 4 + crouton conventions instead of WCAG. Reviews just your diff (or a package/file) for v3 component names, the v4 overlay pattern, Options API, raw-HTML re-implementations, and hardcoded colors; rates findings by severity; and either comments inline on the PR (--comment) or applies the safe fixes for you (--fix). Steers the depth-aware `frontend-review` subagent. Use when asked to "check the frontend", "are we using Nuxt UI right", "review component usage", "frontend-review this", or run /frontend-review.
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。
Adversarially probe this monorepo for security flaws at the right depth. Steers the red-team subagent — picks quick/standard/deep from the request, spawns it (fanning out for a wide deep sweep), collates findings into a dated report, and files security/sec:* issues for confirmed high/critical findings. Use when asked to "red-team", "try to hack this", "find security holes", "pentest this package/app", or as the brain behind the CI + daily security runs.
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。
Bulk extract content from an entire website or site section. Use this skill when the user wants to crawl a site, extract all pages from a docs section, bulk-scrape multiple pages following links, or says "crawl", "get all the pages", "extract everything under /docs", "bulk extract", or needs content from many pages on the same site. Handles depth limits, path filtering, and concurrent extraction.
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。
Default material, information-density hierarchy, clean-rendering, negative-prompt hygiene, and evidence-preserving photo-repair layer for IM2 / GPT Image 2 / gpt-image-2 / image_gen. Use for clean generation/redraws, artifact cleanup, focal-detail control, atmospheric depth, physically coherent light paths, air scattering, volumetric light, light ratio, material realism, architecture/terrain/hard-surface scene mass and structural grounding, and 企业/公司活动/门店/团队合影/商品/餐饮/证件文档照片修复. Preserve identity, headcount, placement, product facts, text, logo, QR, date, price, and scene evidence; prefer residual blur over invented restoration detail.
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。
Reconstruct an evidenced indoor space from local Realsee scan exports, point clouds, CAD, and panoramas as a separately editable native Blender scene. Use for scan-to-Blender space modeling, source-based geometry/material/light refinement, and requested walkthrough or physics exports. Argus panorama-to-depth inference is a separate capability.
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 to process one to 99 local exact 2:1 equirectangular panorama images with Realsee Argus, producing depth maps, a merged GLB point cloud, camera poses, optional intrinsics, and a validated local output index. Trigger for Argus panorama reconstruction, Argus ZIP input, or explicit Argus start/status/collect lifecycle requests. Do not trigger for panorama editing or stitching, arbitrary-photo 3D generation, existing GLB inspection, or research-only questions.
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。
Web and App implementation guide for 3D UI. Trigger when user wants actual 3D objects, perspective effects, and spatial depth.
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 intrusion activity against the Lockheed Martin Cyber Kill Chain framework to identify which phases an adversary has completed, where defenses succeeded or failed, and what controls would have interrupted the attack at earlier phases. Use when conducting post-incident analysis, building prevention-focused security controls, or mapping detection gaps to kill chain phases. Activates for requests involving kill chain analysis, intrusion kill chain, attack phase mapping, or Lockheed Martin kill chain framework.
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。
Defense-in-depth security across Rust, TypeScript, and Bash for the Pump SDK — cryptographic key handling, memory zeroization, secure file I/O, input validation, privilege management, dependency auditing, and a 60+ item security checklist.
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 vocabulary for designing deep modules, interfaces, seams, adapters, leverage, and locality. Use when designing or reshaping module boundaries, making code more testable, or evaluating interface depth.
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 explaining a technical concept and adapting depth, pacing, and examples to the learner's readiness.
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。
Knowledge base from NIST Secure Software Development Framework (SSDF) v1.1 (SP 800-218). Use for secure software development practices, SDLC security integration, software supply chain security, vulnerability disclosure, SBOM, threat modelling, secure coding, build hardening, EO 14028 compliance. Covers the four SSDF practice groups (PO, PS, PW, RV) only; does not cover NIST CSF, SP 800-53 controls, or cloud-specific security frameworks in depth.
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Knowledge base from NIST SP 800-160 Vol 1 (Engineering Trustworthy Secure Systems) and Vol 2 (Developing Cyber-Resilient Systems). Use for systems security engineering (SSE): the three SSE framework contexts (problem/solution/trustworthiness), the 30+ design principles for trustworthy secure design, trustworthiness and assurance/assurance cases, security across the ISO/IEC/IEEE 15288 life-cycle process groups, and the Vol 2 cyber-resiliency engineering framework — 4 goals (anticipate/withstand/recover/adapt), objectives, 14 techniques, implementation approaches, and design principles for the APT/adverse-conditions threat model. Bridges systems engineering and the NIST security cluster (CSF/SSDF/RMF). Does not reproduce ISO/IEC/IEEE 15288 process text, nor cover SP 800-53 control catalogs in depth.
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。
Knowledge base from NIST AI Risk Management Framework 1.0 (NIST AI 100-1). Use for AI risk management, trustworthiness characteristics, GOVERN/MAP/MEASURE/MANAGE functions, bias management, AI actor roles, TEVV, AI RMF profiles, and socio-technical risk framing. Does not cover sector-specific regulations, EU AI Act, ISO 42001 in depth, or the AI RMF Playbook tactical detail.
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。
Knowledge base from NASA-STD-8719.14C (Process for Limiting Orbital Debris). Use for orbital-debris assessment planning, mission-related debris limits, explosion/passivation and collision risk, postmission disposal options, reentry casualty risk, and ODAR/EOMP governance. Covers STD-8719.14C (Approved 2021-11-05) synthesized notes only; does not replace NPR 8715.6 delivery timing, NASA-HDBK-8719.14 environment/modeling depth, or program-specific OSMA waivers.
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。
Knowledge base from the SD-22 DMSMS Guidebook (DSPO, FY24 working draft). Use for managing Diminished Manufacturing Sources and Material Shortages (DMSMS) and obsolescence across a long-lived system's life cycle: the five-step process (Prepare, Identify, Assess, Analyze, Implement) plus the Strategize overlay; standing up a DMSMS Management Team (DMT) and Management Plan (DMP); risk-based monitoring and surveillance (the risk cube, predictive tools, vendor surveys, GIDEP/DLA PDNs, critical-materials analysis); health assessments and resolution timing; costing and selecting resolutions (life-of-need buys, substitutes, redesign, technology refreshment) by AoA/BCA; and budgeting/executing resolutions through modification funding and the ECP process. Defense-sustainment / DoD-acquisition framing throughout. Does NOT teach general systems engineering, parts-management standards, or contracting law in depth, and does not reproduce DoD policy text or the source's tables and figures.
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。
Knowledge base synthesized from the Guide to the Systems Engineering Body of Knowledge (SEBoK) v2.14 by the BKCASE Project. Use for the established systems-engineering canon: SE fundamentals and foundations (systems science, systems thinking, the systems approach, modelling/MBSE), the life cycle (ISO/IEC/IEEE 15288/24748/24774 process, development & agile approaches, model selection/tailoring), technical management, concept definition, architecture/realization (the Vee), V&V, maintenance/sustainment, SE standards, and the application contexts (product, service, enterprise, systems-of-systems, healthcare), plus enabling SE (business/team/individual), related disciplines, quality attributes/specialty engineering, implementation examples, and emerging knowledge. Good for grounding background, vocabulary, and prior-art positions across all eight SEBoK Parts. SCOPE LIMITS: this pack is SEBoK v2.14 only (released 2026-05-18); it synthesizes and signposts rather than reproducing the source — it does not reproduce ISO/IEC/IEEE standard text, is a curated guide (not a complete textbook), and is thin on AI-integration depth (Part 8 is a staging area, not settled practice). LICENCE: content is CC BY-NC-SA 3.0 — non-commercial use only, attribution to the BKCASE Project required, share-alike obligations carry forward.
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。
Knowledge pack from 'Towards Digital Engineering: The Advent of Digital Systems Engineering' (Huang et al., Old Dominion University, arXiv:2002.11672, 2020). Use when reasoning about digital engineering, the DoD Digital Engineering Strategy and its five goals, the Authoritative Source of Truth, digitalization vs. digitization, digital augmentation, digitalized models, provenance, unique identification, and the four-level (vision/strategy/action/foundation) DSE research framework. Covers the conceptual/vision layer of the field. SCOPE LIMITS: this is a single ~28-page vision paper, not a methods handbook — it is thin on step-by-step procedures, tooling, case studies, and quantitative evaluation, and it predates 2020 so it does not cover later digital-engineering standards or recent AI/LLM advances. Use the sebok pack for established SE canon and MBSE depth.
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。
Knowledge base from the NASA Cost Estimating Handbook (CEH) v4.0. Use for NASA's 12-step, three-part cost estimating process (Project Definition, Cost Methodology, Cost Estimate); the WBS, CADRe, and ONCE data backbone; estimating methodologies (analogy, parametric/CER, engineering build-up, EVM, Delphi); ground rules and assumptions, data normalization and inflation (BY/CY/RY); the point-estimate-to-S-curve cost-risk chain and Unallocated Future Expense (UFE) reserves; Joint Cost and Schedule Confidence Level (JCL) analysis via probabilistic cost-loaded schedules; decision-support analyses (sensitivity, trade studies, make/lease-vs-buy, affordability, CAIV); and economic analysis (discounting, NPV, OMB Circular A-94). The cost-estimating complement to NASA's SE and risk packs. Does NOT reproduce the handbook's tool-specific procedures, worked examples, or appendix-depth methods (it names the appendices), nor cover full DoD/GAO cost guides, schedule construction, or formal risk management beyond the cost interface.
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。
Knowledge base from NASA Risk Management Handbook (NASA/SP-2011-3422). Use for risk-informed decision making, continuous risk management, performance commitments, risk scenario diagrams, risk disposition types, risk burn-down schedules, objectives hierarchies, deliberation and alternative selection, risk driver identification, and RM planning for space and safety-critical programmes. Does not cover domain-specific PRA methods (fault trees, event trees) in procedural depth — see NASA PRA Procedures Guide for those.
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。
Knowledge base from the GAO Cost Estimating and Assessment Guide (GAO-20-195G). Use for program cost estimating: the four characteristics of a reliable estimate (comprehensive, well documented, accurate, credible) and the 18 best practices; the 12-step cost estimating process (purpose, plan, technical baseline, WBS, ground rules and assumptions, data, point estimate, sensitivity, risk/uncertainty, document, present, update); estimating methods (analogy, parametric, engineering build-up, learning curves); Monte Carlo risk/uncertainty analysis, confidence levels and contingency; auditing and validating an estimate against the characteristics; earned value management (EIA-748, BCWS/BCWP/ACWP, CPI/SPI/TCPI, EAC, PMB, IBR); and specialized techniques (software cost estimating, learning curves, Analysis of Alternatives, WBS templates, the Green Book internal-control framework). This is the cost-estimating companion to the GAO Schedule and Technology Readiness Assessment guides. Does not cover schedule estimating/risk in depth (see the GAO Schedule Assessment Guide), agency-specific cost models, or the full text of referenced standards (EIA-748, MIL-STD-881D, the Green Book) — these are named, not reproduced.
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。
Knowledge base from NASA NPR 7123.1D — Systems Engineering Processes and Requirements. Use for the 17 common SE processes (SE Engine), life-cycle reviews and entrance/success criteria, SEMP structure and content, ETA roles and tailoring/customizing rules, Technology Readiness Levels (TRL 1–9), SE work product maturity terminology, contracted project oversight, and MOE/MOP/TPM measurement frameworks. Does not cover NASA programme financial management, human spaceflight medical standards, or software engineering requirements in depth (see NPR 7150.2 for the latter).
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。