muse
免费Defining and managing design tokens, applying token systems to existing codebases, building design system foundations. Use for spacing, color, typography, dark mode, cross-platform output.
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Defining and managing design tokens, applying token systems to existing codebases, building design system foundations. Use for spacing, color, typography, dark mode, cross-platform output.
中文简介正在准备中。当前显示原文说明。
Implementing production iOS/Android/macOS native features (SwiftUI, Compose) and iterating a screen against a reference design. Not for cross-platform RN/Flutter (Forge prototypes only; production is out of scope) or web (Artisan).
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Orchestrating multi-specialist task chains and scope-adaptive product delivery: classifies intent, selects and executes the minimum viable chain, aggregates results, and verifies acceptance criteria. For multi-domain tasks, build-first delivery, and product lifecycle execution.
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Designing and evaluating AI/ML systems: prompt engineering, RAG design, LLM application patterns, AI safety, evaluation frameworks, MLOps, cost optimization. Use for AI pipelines or eval harnesses.
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Auditing AI CLI configs and designing, configuring, or debugging Claude Code hooks. Use for Codex/agy/Claude Code config reviews, hook lifecycle automation, quality gates, MCP governance, personal dotfiles/shell setup, or macOS AppleScript/JXA automation.
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Reviewing code via multi-engine orchestration (Claude + Codex) on three axes — secure, correct, and lean — shipping only findings worth fixing. Use for PR review or pre-commit. Complements Zen.
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Designing cryptographic architecture: algorithm selection, key management, E2EE, KMS integration, signature verification, TLS. Use when designing crypto protocols or key rotation flows.
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Designing A/B tests: hypothesis docs, sample size, feature flags, significance analysis, CUPED, SRM detection, switchback experiments. Use when hypothesis validation is needed.
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Conducting user research: interview guides, usability test plans, qualitative analysis, persona creation, journey mapping. Use when research design or analysis is needed; complements Echo.
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Implementing CSS/JS animations for hover effects, loading states, modal transitions, and gesture interactions. Use for meaningful motion, interaction feedback, or performance-safe animation.
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Controlling combinatorial explosion across multi-dimensional axes: minimum coverage sets, execution plans, test/deploy/UX/risk prioritization. Use when scoping multi-axis combinations.
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Enumerating failure modes via pre-mortem analysis. Systematically identifies failure scenarios for plans, designs, and features, scoring them with RPN/AP. Does not write code.
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Orchestrating ecosystem self-evolution: lifecycle-phase detection, agent relevance, cross-agent knowledge synthesis, evolution proposals. Use when auditing skill-ecosystem health or fitness.
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Running autonomous loops for nexus-autoloop. Generates script sets from goals, designs operation contracts, audits live loops, and recovers state — runners that complete reliably.
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Designing new skill agents via gap analysis, overlap detection, SKILL.md + reference generation, and Nexus integration. Not for task orchestration (Nexus) or format-only audits (Gauge).
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Navigating the skill ecosystem and guiding onboarding. Lists agents, recommends best fit for tasks. Don't use for task execution (Nexus), agent design (Architect).
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Orchestrating design-to-implementation pipelines (code to visual to code closed loop), persisting a project design system across agents. Not for a single prototype (Forge) or direction only (Vision).
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Designing and auditing repository structure for humans and LLM agents: layouts, monorepos, docs/tests/scripts, progressive disclosure, prompt-cache topology, and safe migrations.
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Curating cross-agent knowledge and institutional memory: extracts patterns from agent journals into METAPATTERNS.md, detects knowledge decay, propagates best practices. Use for memory curation.
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Implementing production frontend code for React/Vue/Svelte: hooks design, state management, Server Components, form handling, data fetching. Converts Forge prototypes to production quality.
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Analyzing dependencies, circular references, and God Classes; authoring ADRs/RFCs. Use for architecture improvement, module decomposition, and technical debt assessment.
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Verifying spec compliance: extracts ACs from specs, adversarially checks conformance, generates BDD scenarios and traceability matrices. Use when impl must be proven to match a PRD/SRS/AC.
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Engineering observability and reliability: SLO/SLI design, distributed tracing, alerting, dashboards, capacity planning, toil automation, reliability review. Use for instrumentation or SLO definition.
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Optimizing frontend (re-render, memoization, lazy loading) and backend (N+1, indexing, caching, async) performance, plus continuous auto-tuning loops for GC/threadpool/cache/worker settings.
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