Research best practices via MCP Ref/Context7/WebSearch and create documentation (guide/manual/ADR/research). Single research, multiple output types.

Top orchestrator for complete doc system. Delegates to ln-110 coordinator (project docs via 5 L3 workers) + ln-120-150 workers. Phase 4: global cleanup. Idempotent.

Creates reference documentation structure + smart documents (ADRs/Guides/Manuals) based on TECH_STACK. Only creates justified documents (nontrivial technology choices). L2 Worker in ln-100-documents-pipeline.

Creates test documentation (testing-strategy.md + tests/README.md). Establishes testing philosophy and Story-Level Test Task Pattern. L2 Worker in ln-100-documents-pipeline workflow.

Builds interactive HTML presentation with 6 tabs (Overview, Requirements, Architecture/C4, Tech Spec, Roadmap, Guides). Creates presentation/README.md hub. L2 Worker under ln-100-documents-pipeline.

Traffic-First opportunity discovery. KILL funnel filters ideas by traffic channel, demand, competition, revenue, interest, MVP-ability. Outputs one idea + one channel recommendation.

Validates Stories/Tasks with GO/NO-GO verdict, Readiness Score (1-10), Penalty Points, and Anti-Hallucination verification. Auto-fixes to reach 0 points, delegates to ln-002 for docs. Use when reviewing Stories before execution or when user requests validation.

L3 Worker. Reviews task implementation for quality, code standards, test coverage. Creates [BUG] tasks for side-effect issues found outside task scope. Sets task Done or To Rework. Usually invoked by ln-400 with isolated context, can also review a specific task on user request.

Fixes tasks in To Rework and returns them to To Review. Applies reviewer feedback only for the selected task.

Runs a single Story final test task (label "tests") through implementation/execution to To Review.

Story-level quality orchestrator with 4-level Gate (PASS/CONCERNS/FAIL/WAIVED) and Quality Score. Pass 1: code quality -> regression -> manual testing. Pass 2: verify tests/coverage -> calculate NFR scores -> mark Story Done. Use when user requests quality gate for Story or when ln-400 delegates quality check.

Worker that checks DRY/KISS/YAGNI/architecture compliance with quantitative Code Quality Score. Validates architectural decisions via MCP Ref: (1) Optimality - is chosen approach the best? (2) Compliance - does it follow best practices? (3) Performance - algorithms, configs, bottlenecks. Reports issues with SEC-, PERF-, MNT-, ARCH-, BP-, OPT- prefixes.

Orchestrates test planning pipeline (research → manual → auto tests). Coordinates ln-511, ln-512, ln-513. Invoked by ln-500-story-quality-gate.

Performs manual testing of Story AC via executable bash scripts saved to tests/manual/. Creates reusable test suites per Story. Worker for ln-510.

Plans automated tests (E2E/Integration/Unit) using Risk-Based Testing after manual testing. Calculates priorities, delegates to ln-301-task-creator. Worker for ln-510.

Audit project documentation quality across 8 categories (Hierarchy, SSOT, Compactness, Requirements, Actuality, Legacy, Stack Adaptation, Semantic Content). Delegates to ln-601 for deep semantic verification of project documents. Use when documentation needs quality review, after major doc updates, or as part of ln-100-documents-pipeline. Outputs Compliance Score X/10 per category + Findings + Recommended Actions.

Semantic content auditor (L3 Worker). Verifies document content matches stated SCOPE, aligns with project goals, and reflects actual codebase state. Called by ln-600 for each project document. Returns scope_alignment and fact_accuracy scores with findings.

Audit code comments and docstrings quality across 6 categories (WHY-not-WHAT, Density, Forbidden Content, Docstrings, Actuality, Legacy). Use when code needs comment review, after major refactoring, or as part of ln-100-documents-pipeline. Outputs Compliance Score X/10 per category + Findings + Recommended Actions.

Coordinates 9 specialized audit workers (security, build, architecture, code quality, dependencies, dead code, observability, concurrency, lifecycle). Researches best practices, delegates parallel audits, aggregates results into single Linear task in Epic 0.

Architecture audit worker (L3). Checks DRY (7 types), KISS/YAGNI, layer breaks, error handling, DI patterns. Returns findings with severity, location, effort, recommendations.

Code principles audit worker (L3). Checks DRY (7 types), KISS/YAGNI, TODOs, error handling, DI patterns. Returns findings with severity, location, effort, recommendations.

Code quality audit worker (L3). Checks cyclomatic complexity, deep nesting, long methods, god classes, O(n²) algorithms, N+1 queries, magic numbers, decentralized constants, duplicate constants. Returns findings with severity, location, effort, recommendations.

L3 Worker. Analyzes single pattern implementation, calculates 4 scores (compliance, completeness, quality, implementation), identifies gaps and issues. Usually invoked by ln-640, can also analyze a specific pattern on user request.

L3 Worker. Audits architectural layer boundaries, detects violations (code in wrong layers), checks pattern coverage. Invoked by ln-640 once per audit.

Coordinates project structure migration to Clean Architecture

Coordinates Docker, CI/CD, and environment configuration setup via auto-detection

Configures structured logging (Serilog/.NET, structlog/Python)

Run and interact with lnd Lightning Network daemon in Docker. Use for Lightning development, testing payment channels on regtest, managing lnd containers, and calling lnd RPC endpoints (getinfo, connect, open/close channels, pay/receive). Supports bitcoind, btcd, and neutrino backends.

Configure and deploy load balancers (HAProxy, AWS ELB/ALB/NLB) for distributing traffic, session management, and high availability.

When distributing traffic across multiple servers or regions, use this skill to select and configure the appropriate load balancing solution (L4/L7, cloud-managed, self-managed, or Kubernetes ingress) with proper health checks and session management.

load-context

| Atributo | Valor |

Create and manage K6 load tests for REST and GraphQL APIs. Use when creating load tests, writing K6 scripts, testing API performance, debugging load test failures, or setting up performance monitoring. Covers REST endpoints, GraphQL operations, data generation, IRI handling, configuration patterns, and performance troubleshooting.

Auto-activates when user mentions load test, performance test, stress test, k6, Artillery, benchmark, or scalability testing. Expert in designing and executing performance tests.

LobeChat - Open-source AI agent workspace with multi-provider LLM support, plugin system, knowledge base RAG, 505+ agents, and self-hosting options via Docker/Vercel

LobeHub CLI Toolbox - AI-powered command-line tools including lobe-commit (ChatGPT Git commits with Gitmoji), lobe-i18n (automated internationalization), and lobe-label (GitHub label management)

Delegate complex, multi-step codebase exploration to local Ollama models. Best for analysis, review, and understanding tasks that require reasoning across multiple files.

Local development environment context management

Local Development Standards define how developers set up and run projects on their machines, ensuring consistency, reproducibility, and minimal onboarding friction.

Local Kubernetes development with EKS parity using Kind, LocalStack for AWS services, and local Keycloak for authentication testing

local-finetune

Local Frappe development environment for testing APIs before production deployment. Use when developing or testing Python/API changes locally.

Review current changes against project guidelines before PR

Use when code changes touch database, cache, queue, or other service-dependent components - enforces testing against real local services instead of mocks

Comprehensive guide for using Local Skills MCP - creating skills in the right locations, understanding skill directories, setup, and configuration. Use when creating new skills, deciding where to save skills, setting up the MCP server, or understanding how skill aggregation works.

Test local Jekyll build and visualize pages using Playwright MCP. Starts the development server, navigates through key pages, captures screenshots, and validates rendering. Use when testing local changes before deployment.

Audit a skill against Anthropic skill-creator standards

Run local AI models with LocalAI. Deploy OpenAI-compatible API for LLMs, embeddings, audio, and images. Use for self-hosted AI, offline inference, and privacy-focused AI deployments.

Specialized in multi-language support (i18n) for Gravito. Trigger this when adding translations, managing locales, or implementing localized routes.