'engineering' 검색 결과

Find and identify the CAttributeList_SetOrAddAttributeValueByName function in CS2 server binary using IDA Pro MCP. Use this skill when reverse engineering CS2 server.dll or libserver.so to locate the econ attribute-list workhorse that sets an existing float attribute by name or appends a new one. Resolved via a durable caller anchor: the weapon paint-kit/wear/seed/kill-eater applier function, which is itself located by the literal econ keyvalue-system strings "set item texture prefab" / "set item texture wear" / "set item texture seed". This function backs weaponpaints-style plugins that programmatically set an econ item's paint kit / wear / seed / stickers. Trigger: CAttributeList_SetOrAddAttributeValueByName, SetOrAddAttributeValueByName

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Find and identify the CBaseEntity_GetChangeAccessorPathInfo_1 virtual function in CS2 binary using IDA Pro MCP. Use this skill when reverse engineering CS2 server.dll or libserver.so to locate the second GetChangeAccessorPathInfo override by scanning CBaseEntity vtable slots near the known CBaseEntity_GetChangeAccessorPathInfo_2 slot for an implementation identical to CBaseEntity_GetChangeAccessorPathInfo_2. Trigger: CBaseEntity_GetChangeAccessorPathInfo_1

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Find and identify the CGameSceneNode::GetSkeletonInstance virtual function's vtable slot, plus the CBaseAnimGraph::m_skeletonInstance and CSkeletonInstance::m_animationController struct member offsets, in the CS2 server binary using IDA Pro MCP. Use this skill when reverse engineering server.dll or libserver.so to locate the scene-node accessor that returns a node's CSkeletonInstance* (or null if the node isn't a skinned model), and the two related struct-member offsets used by CounterStrikeSharp's animation-graph memory patches. Trigger: CBaseAnimGraph_m_skeletonInstance, CGameSceneNode_GetSkeletonInstance, CSkeletonInstance_m_animationController

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Use when designing or improving prompts, commands, hooks, skills, or sub-agent instructions, including output quality, reliability, and token efficiency.

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AIエージェントが実装出力の大部分を生成するチームのためのエンジニアリング運用モデル

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評価ファーストの実行、分解、コスト考慮型モデルルーティングによるエージェンティックエンジニアとしての運用

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Use when Spark engineering knowledge must be placed, deduplicated, migrated, or validated across AGENTS, Notes, Roles, Skills, and Workflows.

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Directs pixel art that must read at several zoom scales at once — per-scale palette and silhouette rules, terrain-versus-unit contrast, a one-scene look test, and briefs for an artist or image generator. Trigger when a game renders one world through zoom bands or levels of detail, a pixelated 3D or 2.5D band with billboards included; when a sprite, unit or icon vanishes against terrain zoomed out; for a cross-band look test or pixel-art style guide; or say pixelsmith (test, brief, audit, 3d). Works from a described scene. Drawing is an art tool's job; rendering and LOD code the game's engineering; a brand palette brandscribe's; game audio soundsmith's.

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Researches a question to something usable — a verdict with a flip condition, a versioned playbook or a graded report — every claim tagged by evidence. Trigger on which X should I pick (even from pasted pages), is Y worth it, compare A vs B, go/no-go, research this, deep research, fact-check a doc, write or merge a reference guide or playbook, grade a research report, read a bot-blocking source (Reddit, YouTube, X), or map an unfamiliar repo before contributing (entry points, flows, where to change X); or say researchscribe (verdict, playbook, research, verify, sources, map, refresh). Code review is engineering tooling's; fiction canon is lorescribe's; messages commscribe's; prompt model picks promptwright's; skill niches skillwright's; config rigwright's; brands brandscribe's.

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Expert in 3D computer vision labeling tools, workflows, and AI-assisted annotation for LiDAR, point clouds, and sensor fusion. Covers SAM4D/Point-SAM, human-in-the-loop architectures, and vertical-specific training strategies. Activate on '3D labeling', 'point cloud annotation', 'LiDAR labeling', 'SAM 3D', 'SAM4D', 'sensor fusion annotation', '3D bounding box', 'semantic segmentation point cloud'. NOT for 2D image labeling (use clip-aware-embeddings), general ML training (use ml-engineer), video annotation without 3D (use computer-vision-pipeline), or VLM prompt engineering (use prompt-engineer).

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ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.

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Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing.

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Turn a one-line objective into a step-by-step construction plan for multi-session, multi-agent engineering projects. Each step has a self-contained context brief so a fresh agent can execute it cold. Includes adversarial review gate, dependency graph, parallel step detection, anti-pattern catalog, and plan mutation protocol. TRIGGER when: user requests a plan, blueprint, or roadmap for a complex multi-PR task, or describes work that needs multiple sessions. DO NOT TRIGGER when: task is completable in a single PR or fewer than 3 tool calls, or user says "just do it".

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Core UI/UX engineering skill for building highly interactive, spatial, weightless, and glassmorphism-based web interfaces using GSAP and 3D CSS.

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Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.

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React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

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Diagnose and improve humor using systems thinking. Use when jokes fall flat, when humor feels forced, when punchlines don't land, or when you want to systematically enhance comedic writing. Treats jokes as engineerable connection systems.

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2025年最前沿的AI原生开发范式——VibeCoding。覆盖：Prompt-to-Product工作流、多轮对话管理、AI编码助手协作策略、代码质量保障、v0.dev/Lovable/Claude Code/Replit Agent工具链集成。触发词：vibecoding、VibeCoding、AI原生开发、提示即产品、AI pair programming、conversation-driven coding、prompt engineering for products

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Write strategy-oriented Product Requirements Documents (PRDs) for AI product managers. Use when: (1) drafting a new PRD or strategy doc, (2) structuring a feature proposal with strategy rationale, (3) writing requirement docs that emphasize "why" over "how", (4) turning raw product ideas into structured requirement documents. NOT for: purely technical specs, engineering tickets, or UI copy.

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Build and ship software — code, implement, develop, API, backend, frontend, deploy, infrastructure, CI/CD, databases, cloud, mobile, AI/ML. The CTO office's broadest execution domain, applied with TDD discipline.

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AI video and image prompt engineering — video generation, image generation, product video, social media video, cinematic direction, animation, Seedance, Higgsfield, GPT-Image-2. Applies 15 Maxim-authored cinematic styles and the atomic prompt schema.

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Apply GDPR-compliant engineering practices across your codebase. Use this skill whenever you are designing APIs, writing data models, building authentication flows, implementing logging, handling user data, writing retention/deletion jobs, designing cloud infrastructure, or reviewing pull requests for privacy compliance. Trigger this skill for any task involving personal data, user accounts, cookies, analytics, emails, audit logs, encryption, pseudonymization, anonymization, data exports, breach response, CI/CD pipelines that process real data, or any question framed as "is this GDPR-compliant?". Inspired by CNIL developer guidance and GDPR Articles 5, 25, 32, 33, 35.

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Modular orchestration of agent patterns from Anthropic's engineering guide. Intelligently selects and implements prompt chaining, routing, parallelization, orchestrator-workers, evaluator-optimizer, and autonomous agents. Includes pattern combinations and language-specific implementations.

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Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library

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