Loading...
Loading...
Found 176 Skills
Crea documentos técnicos organizados en /docs (specs, planes, ADRs, referencias). Usa cuando el usuario diga "crear documento", "escribir spec", "documentar esto", "creame una spec", "escribime documentación", "hacer documentación", o quiera agregar documentación al proyecto.
Guided, section-by-section authoring of the master architecture document for the game. Reads all GDDs, the systems index, existing ADRs, and the engine reference library to produce a complete architecture blueprint before any code is written. Engine-version-aware: flags knowledge gaps and validates decisions against the pinned engine version.
Finds all REFACTOR markers in codebase, validates associated ADRs exist, identifies stale markers (30+ days old), and detects orphaned markers (no ADR reference). Use during status checks, before feature completion, or for refactor health audits. Triggers on "check refactor status", "marker health", "what's the status", or PROACTIVELY before marking features complete. Works with Python (.py), TypeScript (.ts), and JavaScript (.js) files using grep patterns to locate markers and validate against ADR files in docs/adr/ directories.
Helps engineering managers break down knowledge silos and build sustainable documentation and collaboration practices — produces a four-root-cause diagnostic for silos, an Engineering Guilds framework, a minimum-viable documentation approach using ADRs, a structured onboarding model, and a cross-team request decision framework. Use when the user says "knowledge silos," "reinventing the wheel," "nobody reads docs," "onboarding is bad," "teams don't talk," "documentation culture," "cross-team friction," "information doesn't flow," or "new hires struggle to ramp up."
Validates completeness and consistency of the project architecture against all GDDs. Builds a traceability matrix mapping every GDD technical requirement to ADRs, identifies coverage gaps, detects cross-ADR conflicts, verifies engine compatibility consistency across all decisions, and produces a PASS/CONCERNS/FAIL verdict. The architecture equivalent of /design-review.
Specializes in generating Action-Domain-Responder (ADR) boilerplate for Gravito projects. Trigger this when adding new features or modules using the ADR pattern.
Remove AI-writing patterns from French text and inject voice, personality, and soul. Use when editing, reviewing, rewriting, or cleaning up French content that reads like ChatGPT/Claude output. Humanize, humanise, déslopifier. Detects and fixes 27 patterns: AI vocabulary overuse (crucial, essentiel, notamment, par ailleurs, dans le paysage), anglicisms from English-first models (faire du sens, adresser un problème), copula avoidance, formulaic openings (À l'ère de, Dans le paysage actuel), superficial participle analyses (-ant), em dash overuse, redundant adjective doublets, rule of three, sycophantic tone, typographic tells (curly quotes instead of guillemets). Trigger on: humaniser, déslopifier, rendre plus humain, nettoyer le texte IA, enlever le slop, réécrire pour que ça sonne humain, make it sound human.
Use when working on Laminar demands via the remote Laminar MCP and you see wrong or empty client/product scope, plans from source-context lists without per-id loads, needless raw transcripts, same-step or same-release story-map peers, anchored ADR conflicts, MCP transitions/assignments, broken or silent MCP, or mentions of Laminar MCP, demands, TAL-* ids, story map, anchored or source context, or Laminar handoff.
This skill should be used when content teaches patterns (skills, subagents, ADRs, PHRs, specifications) that have canonical sources elsewhere. Prevents format drift by ensuring content references and follows the authoritative format from canonical sources. Use before implementing lessons that teach platform patterns, or when reviewing content for format consistency.
Technical leadership guidance for engineering teams, architecture decisions, and technology strategy. Includes tech debt analyzer, team scaling calculator, engineering metrics frameworks, technology evaluation tools, and ADR templates. Use when assessing technical debt, scaling engineering teams, evaluating technologies, making architecture decisions, establishing engineering metrics, or when user mentions CTO, tech debt, technical debt, team scaling, architecture decisions, technology evaluation, engineering metrics, DORA metrics, or technology strategy.
Knowledge base for designing, reviewing, and linting agentic AI infrastructure. Use when: (1) designing a new agentic system and need to choose patterns, (2) reviewing an existing agentic architecture ADR or design doc for gaps/risks, (3) applying the lint script to an ADR markdown file to get structured findings, (4) looking up a specific agentic pattern (prompt chaining, routing, parallelization, reflection, tool use, planning, multi-agent collaboration, memory management, learning/adaptation, MCP, goal setting, exception handling, HITL, RAG, A2A, resource optimization, reasoning techniques, guardrails, evaluation, prioritization, exploration/discovery). All rules and guidance are grounded in the PDF "Agentic Design Patterns" (482 pages).
Expert technical documentation specialist for developer docs, API references, and runbooks. Activate on: documentation, docs, README, API reference, technical writing, user guide, runbook, ADR, changelog, release notes, tutorial, how-to guide. NOT for: marketing copy (use copywriting skills), blog posts (use content skills), code comments (handled by developers).