本文へ移動
cccskills

「architect」の検索結果

4,516 件 ・ 関連度順

概要と使いどころ

Map the big picture around a topic or software repository by identifying its boundaries, layers, actors, components, relationships, flows, history, fault lines, and open questions, then explain how the pieces fit together and where to look next. Use when a user asks to understand a whole field, domain, technology, ecosystem, industry, codebase, architecture, unfamiliar repo, or phrases such as "give me the big picture", "map the landscape", "how does this all fit together?", "help me get oriented", or "what am I missing?"

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。

tamdogood/builder-essential-skills2242026年8月17日 更新

Use when drafting or revising internal technical design docs, review notes, architecture writeups, or sharing posts in Chinese, especially when the tone should stay evidence-backed, calm, and suitable for peers or leaders rather than marketing or literary writing.

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。

luoling8192/technical-writing2182026年5月27日 更新

Write clear, concise, and accurate technical documentation including API references, user guides, tutorials, changelogs, and architecture docs, tailored to the target audience. Use when the user requests technical writing or provides relevant inputs for this 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。

seb1n/awesome-ai-agent-skills2172026年8月10日 更新

Threat-model and harden AI agents, RAG systems, assistants, and tool-using workflows against direct, indirect, stored, cross-agent, and multimodal prompt injection. Use when reviewing an agent architecture, isolating untrusted content, constraining tools and egress, protecting secrets, adding injection-focused tests, investigating a suspected injection incident, or documenting residual prompt-injection risk.

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。

seb1n/awesome-ai-agent-skills2172026年8月10日 更新

Train machine learning models end-to-end, covering data loading, preprocessing, architecture selection, training loops, validation, and checkpointing. Use when the user requests model training or provides relevant inputs for this 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。

seb1n/awesome-ai-agent-skills2172026年8月10日 更新

Creates Excalidraw diagrams through guided or autonomous workflows. Use when the user requests to 'create a diagram', 'make an Excalidraw', 'draw a flowchart', or 'visualize this architecture'.

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。

bmad-code-org/bmad-builder2162026年9月25日 更新

kb

無料

Manages the Morphir knowledge base under kb/ — OKF bundles and concept documents. Use when adding content to a bundle, creating a new bundle, checking the knowledge base for conformance or provenance drift, building or querying its SQLite index, managing intent through its lifecycle, recording or reading architectural decisions as Decision Records, or navigating, searching and listing its bundles, concepts and links.

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。

finos/morphir2142026年10月17日 更新

Think and work like an expert Mechatronics Engineer. Use when a task calls for Mechatronics Engineer judgment. Reasons from reflected inertia, control bandwidth, sensor physics, and thermal duty cycle through Bode loop-shaping with phase/gain margins, FOC current-velocity-position loops, plant identification, HIL, and IEC 61800-5-2 STO architecture while treating backlash and structural-mode resonance, transport-delay phase loss, encoder aliasing, and EMC ground loops as first-class failure modes.

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。

K-Dense-AI/scientific-agents2142026年10月3日 更新

Think and work like an expert Cytogeneticist. Use when a task calls for Cytogeneticist judgment. Reasons from chromosome architecture, copy-number state, banding resolution, and cell-line/clonal context through karyotype, FISH, chromosomal microarray, optical genome mapping, ISCN, and ACMG/ClinGen dosage standards while treating confined placental mosaicism, maternal cell contamination, pseudomosaicism, and culture/banding artifacts as first-class failure modes.

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。

K-Dense-AI/scientific-agents2142026年10月3日 更新

当需要为 AI 定义工具接口、设计调用规范、实现工具发现与编排机制时调用此 skill。典型场景包括:设计 AI agent 的工具集、定义 JSON Schema/XML/TypeScript 格式的工具描述、实现工具权限控制与并行调度、设计子代理委托架构。 不适用于:定义 AI 身份(persona-design)、安全规则(safety-guardrails)、记忆存储(memory-system)。 关键 trigger 信号:AI 需要调用外部 API 或服务、工具数量超过 10 个需要发现机制、需要区分工具权限层级、需要子代理并行执行、工具调用涉及敏感操作需要审批。

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。

kangarooking/system-prompt-skills2132026年5月4日 更新

Summarize the architecture of code generated by a single retort run. Produces module-level structure, interfaces, and control flow in a form suitable for cross-run comparison — not a full codebase-summary.

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。

adrianco/retort2092026年10月16日 更新

Use this skill when an agent needs production image or video understanding with Amazon Rekognition: labels, objects, scenes, OCR, moderation, image properties, Custom Labels or moderation adapters, stored-video analysis, conditional streaming-video workflows for existing eligible accounts, searchable media libraries, confidence evaluation, S3/IAM/event architecture, privacy, biometric consent, cost control, lifecycle management, and QA.

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。

calesthio/generative-media-skills2052026年7月14日 更新

Provider-independent production workflow for AI agents assembling generated or source media into HyperFrames HTML/CSS/JS videos. Use for HyperFrames composition planning, scene architecture, media custody, animation/timing, captions/audio, deterministic preview/render QA, accessibility/flashing checks, provenance ledgers, and delivery handoff.

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。

calesthio/generative-media-skills2052026年7月14日 更新

Provider-independent production workflow for creating Manim-based explainer animations. Use when an agent must plan, code, render, QA, or hand off precise math, science, data, diagram, algorithm, or concept animations with Manim, including storyboard, scene architecture, formulas, coordinate systems, voiceover timing, accessibility, reproducibility, provenance, and delivery 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。

calesthio/generative-media-skills2052026年7月14日 更新

Guide structured design thinking through 5 progressive levels before any code is written. Levels: Capabilities, Components, Interactions, Contracts, Implementation. Use when building new features, refactoring significant code, designing modules, or when the user says 'design this', 'architect this', 'let's think before coding', 'walk me through the design', or 'whiteboard this'. For simple utilities enter at Level 4 (Contracts), for single-component tasks at Level 2 — see Complexity Calibration. Do not use for quick bug patches.

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。

techygarg/lattice2052026年10月10日 更新

review

無料

Perform a structured code review by composing validation checklists from relevant atoms based on what code changed. Loads atoms conditionally -- clean-code always, architecture/DDD/security/tests only when the delta touches their domain. Produces a severity-ordered report with specific locations and fixes. Use when the user asks to 'review this', 'code review', 'quality check', 'validate the code', 'check my code', 'review the delta', or 'review this PR'.

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。

techygarg/lattice2052026年10月10日 更新

bug-fix

無料

Investigate, reproduce, and safely fix a bug with regression protection. Composes context, diagnosis, architecture, code quality, and testing guardrails into a reproduce-first repair workflow. Use when the user says 'fix this bug', 'debug this', 'investigate this failure', 'patch this regression', 'repair this issue', or 'why is this broken'.

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。

techygarg/lattice2052026年10月10日 更新

Facilitate a structured conversation to create a project-specific knowledge base document. Produces a knowledge-base.md that primes AI with the project's tech stack, architecture, trusted sources, and project structure. Use when the user says 'set up knowledge base', 'prime the project', 'onboard AI', 'create knowledge base', 'set up project context', or 'configure AI 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。

techygarg/lattice2052026年10月10日 更新

Update existing Lattice standards after a significant change — the update-mode counterpart to lattice-init. Scans .lattice/standards/, asks what changed, and routes each affected standard to its refiner's revise mode, recording a git-native change note. Use when the user says 'update refiners', 'refiners update', 'our standards changed', 'update our standards', 'the architecture changed, update the standards', 'we switched languages, update the standards', 'revise standards after a big change', or 're-run the refiners'.

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。

techygarg/lattice2052026年10月10日 更新

Restructure existing code safely without changing externally observable behavior. Composes context, design, architecture, code quality, and testing guardrails into a characterization-first refactoring workflow. Use when the user says 'refactor this', 'clean this up', 'untangle this module', 'move this to the right layer', 'simplify this code', or 'improve this structure'.

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。

techygarg/lattice2052026年10月10日 更新

Generate implementation code from an approved design blueprint or verbal requirements. Composes context anchoring, architecture, clean code, DDD, security, and test quality into an inside-out implementation workflow. Use when moving from design to code, implementing approved contracts, or when the user says 'implement', 'code this', 'build it', 'forge the code', or 'generate the code'.

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。

techygarg/lattice2052026年10月10日 更新

Protocol for handling ambiguous decisions and missing/conflicting knowledge during code generation, design, and review. Ensures AI surfaces genuine judgment calls with structured options and stops on hallucination risk instead of silently assuming. Use when a decision has multiple valid approaches, when facts are missing or contradictory, when the user asks 'what should we do here?', 'is this a judgment call?', 'should I ask about this?', 'am I guessing here?', 'what are the tradeoffs?', or when deciding between two reasonable architectural or design options. Also composed by molecules to define how judgment calls and clarification requests are surfaced and resolved.

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。

techygarg/lattice2052026年10月10日 更新

Resolves rsIDs, navigates RsMergeArch/SNPHistory merge chains, and converts between rsID, SPDI, HGVS, and VCF representations using the dbSNP Build 156 JSON architecture. Use when normalizing variant identifiers, joining variant databases by cluster ID, or tracking deprecated rsIDs through historical merges.

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。

BioTender-max/awesome-bio-agent-skills2022026年7月2日 更新

Reads, validates, and prepares CDISC SDTM and ADaM clinical trial data for analysis. Covers SDTM domain joins (DM, AE, EX, VS, LB, DS), ADaM architecture (ADSL, BDS, OCCDS, ADTTE) with traceability, treatment-emergent AE conventions, baseline derivation, SUPPQUAL/NSV handling, Define-XML 2.1, and Pinnacle 21 / CORE validation. Use when working with clinical trial datasets in CDISC SDTM/ADaM format, preparing analysis-ready data, or validating for regulatory submission.

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。

BioTender-max/awesome-bio-agent-skills2022026年7月2日 更新