'ropa' 검색 결과

Review design specification documents for Go programs before implementation begins. Use this skill when a user has a Go spec, design doc, RFC, or PRD to review, wants feedback on a planned feature in a Go codebase, is about to start implementing from a spec, or asks "is this spec ready?" or "review this before I build it". Applies Go philosophy — simplicity, composition, explicit errors, context propagation — plus Cobra/Viper CLI conventions where applicable.

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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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Pre-implementation red-team analysis. Use when a plan is high-risk, critical path, or expensive to reverse. Challenges plans before code is written — finds edge cases, security holes, scalability bottlenecks, error propagation risks, and integration conflicts. Catches flaws at plan time (10x cheaper than post-implementation).

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Craft CMS 5 content modeling — sections, entry types, fields, Matrix, relations, project config, and content architecture strategy. Covers choosing section types, designing entry types and field layouts, selecting field types, configuring Matrix and nested entries, relations and eager loading, and multi-site propagation.

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Releasing Craft CMS plugins — tagging, Packagist propagation, GitHub releases, branch promotion, shared-library ordering, history rewrites. ALWAYS load when cutting, preparing, verifying, or debugging a plugin release: bumping a version, dating a changelog, creating or moving a git tag, or checking what Packagist serves.

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Idiomatic Go HTTP middleware patterns with context propagation, structured logging via slog, centralized error handling, and panic recovery. Use when writing middleware, adding request tracing, or implementing cross-cutting concerns.

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Design and analysis of combinational and sequential digital circuits using Boolean algebra, truth tables, K-maps, CMOS gate implementation, flip-flops, registers, counters, and finite state machines. Covers De Morgan's theorems, canonical sum-of-products and product-of-sums forms, minimization techniques, propagation delay, setup and hold times, metastability, synchronous design discipline, and FSM encoding. Use when designing, minimizing, verifying, or debugging any circuit whose signals take only discrete logic values.

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Persuasion and rhetorical analysis grounded in classical and modern frameworks. Covers Aristotle's three appeals (ethos, pathos, logos), rhetorical situation (audience, purpose, context), argument structure (Toulmin model), logical fallacies, persuasive writing, propaganda analysis, and ethical persuasion. Use when constructing arguments, analyzing rhetoric, evaluating persuasive messages, detecting fallacies, or studying the relationship between language and power.

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Formal oracle for abductive inference that selects the minimal hypothesis best explaining a set of observations. Provides three sub-oracles: MCMC via monad-bayes, Gemini for natural language, and propagator networks for constraint domains. Use when performing hypothesis selection, explaining observations, or solving inference-to-best-explanation problems.

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VNX-specific domain expertise for the intelligence system, central state databases, and dispatch lifecycle. Use when working on quality_intelligence.db / runtime_coordination.db / dispatch_tracker.db, code_snippets FTS5, snippet_metadata linkage, success_patterns / antipatterns, T0 state projection (t0_state.json), intelligence_injections lifecycle, dispatch → receipt → events → archive flow, central state architecture, project_id propagation across VNX, or any code that reads/writes VNX governance state. Triggers include: editing intelligence injection code, querying central DB for cross-project insights, debugging "intelligence not appearing in T0 state", modifying schema in `schemas/quality_intelligence.sql` or `schemas/runtime_coordination_v*.sql`, working with `scripts/quality_db_init.py` or `scripts/lib/coordination_db.py`.

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VNX-specific domain expertise for the intelligence system, central state databases, and dispatch lifecycle. Use when working on quality_intelligence.db / runtime_coordination.db, code_snippets FTS5, snippet_metadata linkage, success_patterns / antipatterns, T0 state projection (t0_state.json), intelligence_injections lifecycle, dispatch → receipt → events → archive flow, central state architecture, project_id propagation across VNX, or any code that reads/writes VNX governance state. Triggers include: editing intelligence injection code, querying central DB for cross-project insights, debugging "intelligence not appearing in T0 state", modifying schema in `schemas/quality_intelligence.sql` or `schemas/runtime_coordination_v*.sql`, working with `scripts/quality_db_init.py` or `scripts/lib/coordination_db.py`.

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Maintain injected credential authenticators, method-isolated caching, request-context propagation, and the pure-Go SQLite API-key plugin. Excludes interactive portal password authentication and identity-store provisioning.

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Nature-style remote-sensing manuscript reviewer skill for evaluating Earth-observation products, retrievals, machine-learning maps, validation design, uncertainty propagation, spatial transferability and claim-scope calibration.

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Modern C# idioms for any .NET project (C# 10+, .NET 6+): nullable reference types, records, readonly structs, primary constructors, pattern matching, async/await with CancellationToken, IDisposable/IAsyncDisposable, file-scoped namespaces, var usage, naming conventions (PascalCase members, _camelCase fields, I-prefixed interfaces), and class design rules. Apply whenever the project is a .NET 6+ project. Stack-agnostic — referenced by every .NET plugin in the marketplace. Use this skill to: - Write self-documenting immutable value types with records and readonly structs. - Handle nullable reference types explicitly to eliminate NullReferenceException at compile time. - Implement async/await correctly with CancellationToken propagation and ConfigureAwait(false) in libraries. - Dispose unmanaged resources correctly via IDisposable / IAsyncDisposable and using statements. - Apply C# pattern matching (switch expressions, property patterns, list patterns) for cleaner branching logic. Do NOT use this skill for: - Framework-specific idioms (ASP.NET Core controllers, minimal APIs, EF Core — those live in aspnet-core-plugin skills). - Build tooling (dotnet CLI, NuGet, csproj) — see csharp-foundation:dotnet-tooling. - Testing patterns — see csharp-foundation:dotnet-testing.

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Instrument applications with OpenTelemetry for distributed tracing, including auto and manual instrumentation, context propagation, sampling strategies, and integration with Jaeger or Tempo. Use when debugging latency issues in distributed systems, understanding request flow across microservices, correlating traces with logs and metrics for root cause analysis, measuring end-to-end latency, or migrating from legacy tracing systems to OpenTelemetry.

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Implement layered collective defense using alarm signaling, role mobilization, and proportional response. Covers threat detection, alert propagation, immune response patterns, escalation tiers, and post-incident recovery for distributed systems and organizations. Use when designing defense-in-depth where no single guardian covers all threats, building incident response that scales with severity, or when current defense is over-reactive to every alert or under-reactive to genuine threats.

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Automate a professional LinkedIn presence end-to-end using Claude: daily posting with pillar calendar, engagement with anti-detection rules, DM triage, reporting, and growth tracking. Use when the user wants to automate LinkedIn, manage a profile with AI, create a content strategy, or set up engagement automation. Triggers on: "automate my LinkedIn", "LinkedIn automation", "automated LinkedIn", "LinkedIn bot", "LinkedIn scheduling", "LinkedIn AI management", "LinkedIn content calendar", "LinkedIn engagement strategy", "build a LinkedIn presence", "can Claude manage my LinkedIn", "how do I automate my LinkedIn", or any request involving systematic LinkedIn content creation, audience growth, or profile management. Covers: identity/TOV setup, pillar calendar, post creation, engagement rules, anti-detection, scheduled task creation, and weekly reporting.

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Review a Go design spec before implementation begins - dispatch a subagent that checks a design doc for completeness, consistency, and idiomatic Go (simplicity, small consumer-defined interfaces, explicit wrapped errors, context propagation). Use when a user has a Go spec to review, asks "is this spec ready?", or is about to implement from a written design. Distilled from spf13/go-skills and adapted to this repo's conventions.

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Cuts the next release of the unified Prisma CLI: bumps the root package.json version (on the Prisma 8 RC line: 8.0.0-rc.N → rc.N+1), propagates it to every lockstep workspace package, and opens a PR titled "chore(release): bump to <next-version>". When the maintainer merges the PR, the `Publish to npm` workflow ships @prisma/cli-engine and @prisma/cli under dist-tag `latest` (RC versions get a pre-release GitHub Release). Use when a maintainer asks to "cut the next RC", "cut the next release", "bump to the next version", "open a release PR", or "prepare a publish PR".

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Classify a proposed code change as Leaf Node or Core Code to decide how much AI usage and review rigor is appropriate. Use this skill whenever the user asks "is this leaf or core", "what kind of change is this", "should I vibe code this", "can AI write this", "how rigorous should the review be", or before starting any non-trivial change. Also useful as a sub-step inside other workflows (planning, PR prep, code review) when classification matters. Asks 6 diagnostic questions about propagation range, change frequency, tech-debt tolerance, examples, failure cost, and review intensity, then outputs a clear classification with the recommended approach. Trigger even when the user describes a change without explicitly asking for classification — the answer changes how they should proceed.

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Use when a task needs the judgment of a Data Engineer — designing an idempotent pipeline operation so retries and backfills don't corrupt data, choosing event-time over processing-time partitioning for time-series aggregation, enforcing schema compatibility rules before an upstream change propagates downstream, adding automated data quality checks to a pipeline, or deciding between batch and streaming architecture for a specific freshness requirement.

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When a GDD is revised, scans all ADRs and the traceability index to identify which architectural decisions are now potentially stale. Produces a change impact report and guides the user through resolution.

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Email consent management in Marketing Cloud: configuring Subscription Centers, building Preference Centers on CloudPages, enforcing CAN-SPAM and GDPR requirements, and handling opt-out propagation. Trigger keywords: unsubscribe handling, CAN-SPAM compliance, GDPR consent tracking, publication lists, subscription center, preference center, opt-out, double opt-in, Privacy Center, MC consent. NOT for subscriber key and suppression lists — use data/subscriber-data-management. NOT for the CRM consent data model or MC-to-CRM sync — use architect/marketing-consent-architecture.

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Prepares Go applications to work effectively with AI coding agents. Use when setting up a new Go project or retrofitting an existing one to ensure: structured JSON logging (slog/Zap/ZeroLog/Logrus), machine-readable command output, thorough golangci-lint configuration, non-interactive CLI design with --yes flags, structured error handling with meaningful exit codes, proper context.Context propagation, graceful shutdown, health check endpoints, and a standardized Makefile. Triggers when a user asks to make their Go app "agent-ready," "AI-friendly," wants to improve agent tooling/observability in a Go project, or needs to audit an existing Go project against agent-readiness best practices.

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