1.1천건 · 관련도순
6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.
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Confiabilidade da plataforma — SLO, error budget, capacidade, resiliência, ponto único de falha e revisão de prontidão. Use quando o usuário disser "SLA", "SLO", "disponibilidade", "resiliência", "aguenta?", "single point of failure", "production readiness", "quanto de folga temos".
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When the user wants help with paid advertising campaigns on Google Ads, Meta (Facebook/Instagram), LinkedIn, Twitter/X, or other ad platforms. Also use when the user mentions 'PPC,' 'paid media,' 'ROAS,' 'CPA,' 'ad campaign,' 'retargeting,' 'audience targeting,' 'Google Ads,' 'Facebook ads,' 'LinkedIn ads,' 'ad budget,' 'cost per click,' 'ad spend,' or 'should I run ads.' Use this for campaign strategy, audience targeting, bidding, and optimization. For bulk ad creative generation and iteration, see ad-creative. For landing page optimization, see page-cro.
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Strict routing mode for prompts prefixed with `(best)`. USE FOR: any turn where the user explicitly wants the safest, smallest-context, highest-discipline execution path. This skill must route into context-budget-guard first, then continue into the task-specific workflow.
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Audit project and global memory for bloat, stale decisions, duplicates, contradictions, unsafe content, missing provenance, broken routing, and over-budget global files. Load when the user asks to audit memory, clean memory, check memory health, or verify memory quality.
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6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.
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Balances Hi-C contact matrices (ICE via cooler.balance_cooler, KR/SCALE/VC context), computes distance-decay expected with cooltools (expected_cis per-diagonal P(s), expected_trans scalar), builds observed/expected (O/E) matrices, and diagnoses polymer state from the P(s) log-derivative. Covers the within-matrix-vs-cross-sample distinction (balancing is NOT a normalizer), the equal-visibility assumption that CNV/aneuploidy violates (use raw counts for copy-number), cis-only balancing, mad_max/blacklist masking before balancing, multiplicative cooler weights vs divisive juicer weights, and the resolution-vs-depth budget. Use when balancing a .cool/.mcool, computing expected or P(s), making O/E matrices for compartments/loops, deciding ICE vs KR vs SCALE, choosing a resolution for a given depth, or troubleshooting NaN/all-NaN balanced matrices; route cross-sample comparison to hic-differential.
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Plan database migrations before executing them: risk assessment, dependency mapping, multi-service sequencing, rollback budgets, and stakeholder communication plans. Use when deciding HOW to migrate, not when writing the actual DDL. NOT for: writing migration SQL (use database-migration-manager), data ETL pipelines (use data-migration-specialist), query optimization, or ORM configuration.
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Decides HOW to mutate a DAG when a node fails, quality is below threshold, or new information changes the plan. Selects from mutation strategies (add node, replace agent, fork paths, loop back, downgrade model) based on failure type, cost budget, and execution history. Activate on "DAG failed how to fix", "mutation strategy", "replan on failure", "adaptive DAG", "recovery strategy", "what to do when node fails". NOT for detecting failures (use dag-quality), executing mutations (use dag-planner), or runtime execution (use dag-runtime).
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Audit LLM token cost estimates against actual API usage. Activate on 'cost verification', 'token estimate accuracy', 'API cost audit', 'estimation variance'. NOT for pricing lookups, budget planning, or cost optimization strategies.
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Building resilient distributed systems with circuit breakers, retries with full-jitter exponential backoff, retry budgets (per-request 3-attempt + per-client 10% ratio per Google SRE), deadline propagation, and the cascading-failure math (4 layers × 3 retries = 64x amplification). Grounded in Resilience4j, Microsoft Cloud Patterns, AWS Architecture Blog (Marc Brooker), and Google SRE Book. NOT for server-side rate limiting, bulkhead isolation, backpressure protocols, or database-specific retry.
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Audits an Articles of Agreement contract — the daemon-witnessed agreement every official Port Daddy agent signs covering registration, transcript reporting, tool-use gating, file claims, parley conduct, budget limits, and operator control — against the enforcement-beats-hope bar: a clause counts as safe only when it resolves to a concrete, daemon-observable mechanism with a defined denial shape, never a promise the agent might honor. Use when drafting a new agent's Articles, reviewing a compliance-level (C0-C6) claim, deciding whether a clause is genuinely enforced or merely documented, or auditing whether an agent's claimed identity can be trusted. NOT for securing the inbound event-to-spawn path (fleet-event-spawn-trust), designing the relay's transport PKI and signing keys (pd-relay-zero-trust), or tracking an agent's identity and reputation across its whole lifetime after it signs (agent-identity-continuity-reputation).
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Claude Codeセッション全体のエージェント、スキル、MCPサーバー、ルールにわたるコンテキストウィンドウ消費を監査。肥大化や冗長コンポーネントを特定し、優先順位付けされたトークン節約推奨事項を生成。
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Use when adding or updating Spark AI provider models or their compact and preflight metrics, especially baidu-oneapi, Grok, Claude, GPT, DeepSeek, OneAPI, context windows, output budgets, prices, thinking maps, or transports.
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Cost optimization patterns for LLM API usage — model routing by task complexity, budget tracking, retry logic, and prompt caching.
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6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.
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Write competitive research proposals for NSF, NIH, DOE, and DARPA. Agency-specific formatting, review criteria, budget preparation, broader impacts, significance statements, innovation narratives, and compliance with submission requirements.
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Complete personal finance system — budgeting, debt payoff, investing, tax optimization, net worth tracking, and financial independence planning. Use when managing money, building wealth, paying off debt, planning retirement, or optimizing taxes. Zero dependencies.
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Comprehensive ad account analysis across all major platforms (Google, Meta Comprehensive paid advertising audit and optimization for any business type. Performs full multi-platform audits (Google Ads, Meta Ads, LinkedIn Ads, TikTok Ads, Microsoft Ads), single-platform deep analysis, conversion tracking health checks, creative quality assessment, budget allocation optimization, bidding strategy evaluation, and compliance verification. Industry detection for SaaS, e-commerce, local service, B2B enterprise, info products, mobile app, real estate, healthcare, finance, and agency. Triggers on: "ads", "PPC", "paid advertising", "Google Ads", "Meta Ads", "Facebook Ads", "LinkedIn Ads", "TikTok Ads", "Microsoft Ads", "Bing Ads", "ad audit", "campaign audit", "ROAS", "conversion tracking", "creative fatigue", "bid strategy".
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Author and run unattended autonomous workflows — "workflow", "unattended", "run on a schedule", "automate this overnight", "set up an autonomous", "dry-run". Mandatory budget guards, a separate verification gate, idempotency, and dry-run on by default.
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Agency and studio operations — operations, analytics, finance, infrastructure, support, reporting, dashboards, KPIs, budget. Multi-office domain where CTO, CEO and CSO agents converge.
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Blockchain USDC payments via APay — pay services, manage budgets, open streaming channels, and handle x402 protocol.
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Configure and use Honcho memory with Hermes -- cross-session user modeling, multi-profile peer isolation, observation config, dialectic reasoning, session summaries, and context budget enforcement. Use when setting up Honcho, troubleshooting memory, managing profiles with Honcho peers, or tuning observation, recall, and dialectic settings.
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You are an SLO (Service Level Objective) expert specializing in implementing reliability standards and error budget-based engineering practices. Design comprehensive SLO frameworks, establish meaningful SLIs, and create monitoring systems that balance reliability with feature velocity.
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