'dma' 검색 결과

Audit a codebase as a read-only senior advisor, prioritize evidence-backed improvements, and write self-contained implementation plans. Use for codebase audits, improvement roadmaps, focused planning, plan review, plan reconciliation, or executing an existing improve plan through an isolated Codex worktree. The advisor never edits source code; execution uses codex-improve and returns to the main agent for review.

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Bootstrap a new or existing project with a small, file-based documentation system so Claude Code keeps context, lessons, and decisions across session restarts instead of starting cold every time. Sets up a handful of markdown files under .claude/ (standing rules, a free-form note to your next session, a phased roadmap, a prioritized backlog, and searchable history/changelog archives) sized and split so the files read every session stay small while the archives grow without ever costing context. Use this whenever someone is starting a new project and asks how to structure it for long-running AI-assisted work, wants Claude to "remember" things between sessions without relying on chat history, asks for a CLAUDE.md + backlog + changelog setup, mentions "session continuity", "persistent context", "project memory system", or is retrofitting an existing codebase that has no such system yet. Also use to explain or extend an already-bootstrapped bottle system (add a rule, start the archival script, add a new backlog section).

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Use when designing, implementing, reviewing, debugging, testing, profiling, or porting concurrent, parallel, distributed, high-performance, network dataplane, kernel-bypass, or real-time software, including locks, semaphores, monitors, MPI, CSP rendezvous, DPDK, VPP, eBPF, XDP, AF_XDP, SR-IOV, RSS, RoCEv2/RDMA, RMS/EDF, priority inversion, and environment selection from silicon to edge.

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Use when developing, reviewing, debugging, porting, or engineering Linux kernel device drivers, kernel modules, device tree bindings, bus clients, subsystem drivers, DMA/IRQ/memory paths, userspace interfaces, or hardware bring-up plans.

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Use when advising, planning, reviewing, reporting, operating, or improving CTO and technology leadership work across strategy, cybersecurity management, SME/COE, functional and technical requirements, framework selection, people, organization, delivery, risk, KPI, roadmap, budgeting, governance, audit, R&D, stakeholder communication, culture, politics, and sector-specific leadership.

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End-of-life detection for runtimes (Node, Python, Java, Go, .NET) and key packages — surfaces past-EOL items, items reaching EOL within 90 days, and EOL base images for containers. Use when planning a runtime upgrade, auditing for unsupported versions, gating a deploy against EOL deps, or producing a remediation roadmap.

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Load for Blazor/MudBlazor UI changes involving forms, dialogs, focus, keyboard navigation, landmarks, ARIA, color contrast, RTL-safe styling, or WCAG 2.2 AA tests; not for backend-only changes.

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Load when the user asks for CTO advice on feature strategy, architecture direction, build-vs-buy, infrastructure, market positioning, roadmap, self-hosting, cost, or organizational tradeoffs; not for reviewing an existing implementation-plan workstream.

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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).

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Use when the user asks to "optimize our landing page for influencer traffic", "fix our promo-code landing page", or "improve conversion from a creator campaign"; produces a message-match audit, page-structure and social-proof recommendations, a promo-code/CTA conversion plan, and an A/B test roadmap. Not for measuring campaign results after launch — use performance-analyzer. 落地页优化/达人流量转化提升

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Use when the user asks to "track where my emails are actually landing after I send", "read my seed-list inbox vs spam vs promotions results", "trend my Gmail Postmaster / Microsoft SNDS reputation", or "did placement drop after my last send"; produces a per-provider inbox/spam/promotions placement read, a domain/IP reputation trend from Postmaster + SNDS, a send-over-send delta with named regressions, and a reusable SEND-S placement snapshot on your own exported telemetry. Not for the pre-send SPF/DKIM/DMARC auth pre-flight — use deliverability-qa; not for computing the EQS or running the vetoes — use email-quality-auditor. 邮件收件箱落点监测/收件箱vs垃圾邮件/Postmaster声誉趋势

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When the user wants to plan a content strategy, decide what content to create, or figure out what topics to cover. Also use when the user mentions "content strategy," "what should I write about," "content ideas," "blog strategy," "topic clusters," "content planning," "editorial calendar," "content marketing," "content roadmap," "what content should I create," "blog topics," "content pillars," or "I don't know what to write." Use this whenever someone needs help deciding what content to produce, not just writing it. For writing individual pieces, see copywriting. For SEO-specific audits, see seo-audit. For social media content specifically, see social.

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Create a professional paid-advertising strategy covering objectives, economics, platform selection, campaign architecture, audiences, budget, creative, measurement, experiments, governance, rollout, and reporting. Use for ad plan, media plan, PPC strategy, paid-social strategy, campaign architecture, advertising roadmap, or channel planning.

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Use when planning or building a SaaS MVP from scratch. Provides a structured roadmap covering tech stack, architecture, auth, payments, and launch checklist.

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Create an operating policy and roadmap for a live portfolio of Claude Code skills. Use when the user asks to organize, govern, audit, measure, retire, or scale skills already used by a team or repository. Also trigger on "スキルの運用計画", "スキルポートフォリオ", "スキルロードマップ", "スキルを整理して".

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Distill an already-built or near-launch product into one incisive brand kernel — the "reveal" already hiding in its name, story, or the product itself — then build the name, voice, visual identity, and a developer-ready handoff kit around it. This is LATE-STAGE branding: use it when there is a real, thought-through product that is about to launch, or already live but not explained in a way people grasp in an instant. Use whenever the user wants to name or rename a product, find a tagline or slogan, create a brand identity / brand kit / style guide / design system, design a logo, wordmark, palette, or type system, mock up a homepage for a launch, or hand brand assets to a coding agent (Claude Code, Codex, Cursor). Trigger even when the user only says their product needs to "land" or "feel like" something, or that they can't explain it simply yet. Do NOT use for half-baked, pre-product ideas with nothing to excavate — this skill extracts a kernel that already exists; it does not invent one from a blank canvas.

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WCAG implementation: production-level semantic landmark, focus, keyboard, colors. Use when implementing, reviewing or testing wcag implementation for React, Vite, Next.js or Perfect_AI projects.

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Coordinate FriendlyBet company-level strategy, CEO handoff, department orchestration, HR/agent-quality escalation, operating-model decisions, multi-agent synthesis, roadmap tradeoffs, decision rights, quality gates, and updates to the virtual company system. Use when Eyal asks to involve the company, CEO, leadership, strategy, operations, several departments, or named executive agents such as Strategy Director, Chief of Staff, or Operating System Lead.

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Use when working with Aws Ses Deep — advanced AWS SES management including sending quotas, identity verification, configuration sets, dedicated IPs, reputation dashboard, suppression list, email receiving rules, and deliverability advisor. Goes beyond basic SES to cover DKIM/DMARC compliance, event publishing, and virtual deliverability manager.

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MANDATORY prerequisite — load this skill BEFORE every `generate_diagram` tool call. NEVER call `generate_diagram` directly without loading this skill first. Trigger whenever the user asks to create, generate, draw, render, sketch, or build a diagram — flowchart, architecture diagram, sequence diagram, ERD or entity-relationship diagram, state diagram or state machine, gantt chart, or timeline. Also trigger when the user mentions Mermaid syntax or wants a system architecture, decision tree, dependency graph, API call flow, auth handshake, schema, or pipeline visualized in FigJam. Routes to type-specific guidance, sets universal Mermaid constraints, and tells you when to use a different diagram type or skip the tool entirely (mindmaps, pie charts, class diagrams, etc.).

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Consolidate the five tdmcp surveyor reports into one prioritized FEATURE_BACKLOG.md — dedupe cross-surface overlaps, reconcile every candidate against the roadmap (NEW vs planned vs extension), rank by a selectable impact×effort weighting profile into P0/P1/P2 (high-confidence first), and emit per-surface tables + a recommended-next shortlist that hands straight to the build pipeline. Use when a td-synthesizer agent is consolidating surveys during the feature-discovery harness.

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Survey one surface of tdmcp (artist controls, library/packaging, CLI/DX, AI/LLM, or TouchDesigner depth) for candidate NEW features — inventory what exists, cross-check the roadmap, apply the gap-finding lenses, vet each idea, and emit a structured, novelty- and confidence-labelled candidate list to _workspace/discovery/. Use when a td-surveyor agent is scouting a surface during the feature-discovery harness.

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Study a merged or shipped tdmcp implementation and extract reusable learnings: code improvements, runtime/UX lessons, test gaps, docs updates, roadmap items, and harness changes. Use when the user asks to learn from a completed feature/project/PR/build, analyze what can be improved from an implementation, or turn a real installation experience into actionable tdmcp improvements. This is a post-implementation learning harness; it does not replace tdmcp-pipeline for building or tdmcp-quality-audit for broad repo audits.

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Use when brainstorming or planning live event technology, show control, and real-time media systems (TouchDesigner, Resolume, grandMA3).

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