「architecture」の検索結果

Author and manage Architecture Decision Records (ADRs) in docs/specs/. Use when a significant architectural decision needs to be documented.

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Advanced Zephyr RTOS kernel services. Covers inter-thread communication using Zbus (pub/sub), behavioral management with the State Machine Framework (SMF), background processing via work queues, and persistent configuration with the Settings subsystem. Trigger when building modular application architectures, complex state-driven logic, or requiring persistent data storage.

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Skill for building with the Astro web framework. Helps create Astro components and pages, configure SSR adapters, set up content collections, deploy static sites, and manage project structure and CLI commands. Use when the user needs to work with Astro, mentions .astro files, asks about static site generation (SSG), islands architecture, content collections, or deploying an Astro project.

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Maps the 18 OCapN/CapTP/E-rights patterns reinvented piecemeal across codex-rs to their canonical Spritely/Goblins equivalents and the hermes-* bridge skills that formalize each correspondence. Use when auditing capability architecture in codex-rs, planning a Hoot/Goblins port, or reasoning about which E-rights primitive a codex-rs module implicitly implements.

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**Category:** Phase 3 Core - Compositional Architecture

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Botnet architecture taxonomy, detection techniques, and defensive analysis. Covers C2 topologies, DGA analysis, fast-flux detection, P2P overlay mapping, blockchain C2, and ML-based traffic fingerprinting. Defensive research for understanding and countering distributed malicious infrastructure.

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Interact with Axiom.trade -- a Y Combinator-backed (W25) DEX aggregator and trading platform on Solana with Hyperliquid perpetuals integration. Covers API architecture, multi-wallet management, MEV protection, token discovery, and wallet tracking.

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Comprehensive research corpus covering 40+ agentic coordination protocols and ecosystems (MCP, A2A, ANP, UCP, ACP, AGNTCY, NANDA, FIPA, WoT, etc.) with emphasis on identity architectures, governance bodies, and interoperability convergence patterns.

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Anoma intent-centric architecture for cross-chain obstruction passing with Geb semantics and Juvix compilation

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Reference guide for the Twelve-Factor App methodology — 15 principles (12 original + 3 modern extensions) for building portable, resilient, cloud-native applications. Use when evaluating application architecture, designing cloud-native services, reviewing codebases for methodology compliance, advising on configuration, scaling, observability, security, and deployment patterns. Incorporates the 2025 open-source community evolution and cloud-native reinterpretations of each factor.

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Use when facing unknowns, debugging without a clear cause, or making architecture decisions — enforces hypothesis-driven scientific reasoning through observation, hypothesis formulation, prediction, experiment design, and evidence-based conclusion. Use when previous attempts have failed or the problem space involves uncertainty.

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Shared Python 3.11+ development rules — type safety and the boundary policy for `Any` (ty, native generics, Protocol, TypeIs, Pydantic), layered architecture and SOLID, error handling, security, performance, identifier naming, PEP 723 script dependencies, Rich/Typer output, tooling defaults (uv, ruff, ty, hatchling, pytest), and testing requirements (behavioral coverage, TDD). Activates when any Python skill or agent needs the shared rules for implementation, code review, refactoring, or test authoring.

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Routes Python engineering tasks to specialist skills by matching trigger patterns before any architecture, plan, or code is written. Use when working with Typer CLI frameworks, Rich or Textual terminal UIs, CLI UI/UX design, questionary prompts, FastMCP/MCP servers, ty type checker, uv package manager, Hatchling build backend, TOML editing, pre-commit/prek hooks, async Python, PyPI packaging, complex linting, technical debt modernization, testing workflows, feature development, or stdlib-only scripting.

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Guides pytest test architecture for Python 3.11+ using behavioral contracts, risk, and maintenance-adjusted value. Use when choosing unit/integration/property/e2e boundaries, fixture strategy, coverage measurement, or mutation testing. Preserves existing project gates but does not invent test-pyramid ratios, coverage percentages, mutation-score targets, or tests for implementation detail.

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Use when implementing a Python feature, adding CLI commands, writing pytest suites, reviewing Python code, debugging, or refactoring. The primary Python engineering workflow orchestrator — classifies the task and delegates through this plugin's own specialist agents (architect → implement → test → review), sized to the task. Delegates to python-cli-architect (implementation), python-pytest-architect (tests), code-reviewer (review), python-cli-design-spec (architecture). Triggers on any Python task requiring specialist agent coordination or multi-agent execution.

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Autonomous feature research and gap analysis. Use when starting /add-new-feature or analyzing existing architecture documents. Explores codebase patterns, identifies ambiguities, and produces feature-context-{slug}.md for orchestrator RT-ICA phase. Does NOT make technical decisions.

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Trace bugs, CI failures, and unexpected behavior from reproduced evidence to a causal mechanism and governing contract. Distinguish product, architecture, test-oracle, and harness defects; investigate intermittent failures with controlled experiments and report unresolved evidence explicitly.

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Works backward from the stated goal through its prerequisite chain — what must exist to reach the goal, then what each of those requires, back to the current state — classifying each prerequisite as AVAILABLE, DERIVABLE, or MISSING, and blocking planning until nothing is MISSING. Use before creating plans, delegating to agents, or defining acceptance criteria. Activates on specs, PRDs, tickets, RFCs, architecture designs, and multi-step engineering tasks. Always pass `#N` or an inline goal — invoking with no argument and no inline context returns BLOCKED. Integrates with CoVe-style planning pipelines.

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SAM-style feature initiation workflow — discovery through codebase analysis, architecture spec, task decomposition, validation, and context manifest. Use when a user asks to add a feature, plan a feature, or convert an idea into an executable SAM plan.

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Audit documentation claims against implementation and authoritative repository evidence. Use when checking whether README, architecture, configuration, API, usage, or feature documentation is stale, incomplete, contradicted by code, missing implemented behavior, or inconsistent with a normative contract.

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Evaluate and iterate on the SDLC Layer Separation Architecture implementation. Runs validation checks (cross-references, doc completeness, layer metadata, integration points), produces a findings report, and supports iterative fixes. Use when validating first-pass implementation, before claiming layer work is complete, or when improving layer docs/schema.

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Transforms validated /linear-walkthrough artifacts into one presentation-ready deck outline per major codebase component. Use when the user asks to create a presentation, prepare a walkthrough deck, build an onboarding deck, produce an architecture review deck, or summarize a codebase for a technical audience. Requires walkthrough directory output -- reads unified walkthrough, per-section files, validation reports, coverage maps, entry points, and open questions -- then orchestrates four parallel agent phases to produce slide outlines with speaker notes, evidence references, and suggested visuals.

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Produces a structured, end-to-end linear walkthrough of an unfamiliar codebase by orchestrating parallel subagents across four phases — discovery, tracing, validation, and synthesis. Use when onboarding to a new repository, understanding execution paths from entry points, generating navigable codebase documentation, or needing fact-checked coverage of architecture, deployment, testing, and operations.

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Validate and iterate on the SDLC Layer Separation Architecture implementation across the check categories defined in its Evaluation Checklist — cross-references, doc completeness, knowledge-explorer layer filters, research entry metadata, integration points, and plan consistency. Produces a structured findings report and optionally applies safe fixes. Use when validating a first-pass implementation, before claiming layer work complete, auditing layer docs or schema, or running --dry-run to preview findings without changes.

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。