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Found 1,832 Skills
Auto-review pipeline — reads the full CEO, design, eng, and DX review skills from disk and runs them sequentially with auto-decisions using 6 decision principles. (gstack)
Chunk a document into provenance-carrying JSONL ready for embedding via the Nutrient Data Extraction API (`/extraction/parse`, spatial output). Every chunk carries element type, page index, bounding box, confidence, and reading order, traceable to a specific page region. Use for grounded or auditable RAG, cited retrieval, confidence-aware ingestion, or any pipeline that must prove which document region a retrieved answer came from. Triggers include grounded RAG, auditable RAG, RAG with provenance, chunk with bounding box, cite page, provenance-carrying chunks, confidence-aware chunking, or embedding pipeline. Not for cheap Markdown — use document-extraction-api with `--output-format markdown` for that. Not for known target fields — if the user wants specific fields ("invoice number and total", "map to my schema", "return these fields cited"), use document-extraction-api's `extract` (one cited call), not whole-document chunking.
Two primitives of the Nutrient Data Extraction API. `parse` (`/extraction/parse`) returns the whole-document model — a structural JSON of typed elements with bounding boxes, or whole-document Markdown — for RAG ingestion, search indexing, content migration, or layout-aware understanding. `extract` (`/extraction/extract`) returns just the fields you define in a JSON Schema, each with a per-field citation grounding it to a page region. Route to `extract` for "pull the invoice number and total", "extract these fields", "map to my schema", or "with citations"; route to `parse` for "parse this document", "whole-document Markdown", "chunk for embeddings", or "extract every table/element" (no target schema). Triggers include parse this document, extract layout, RAG pipeline, schema extraction, field extraction, cited fields, invoice/form field extraction, document understanding.
Creates useful Mermaid diagrams for SWE, DevOps, and Platform Engineering work — PRs, ADRs, RFCs, runbooks, incident reviews, roadmaps, system architecture, and more. Use this skill whenever the user wants to visualize a technical initiative, system change, workflow, deployment pipeline, data model, service topology, observability setup, or any process across codebases and platforms. Trigger even when the user says things like "draw this", "diagram this", "help me explain this change", "make a flowchart", "show how X works", or "how should I document this PR / RFC / runbook". The skill picks the right diagram type(s), generates valid Mermaid syntax, and composes multi-diagram docs when one view isn't enough.
Diagnose a product's growth model, stage, and current constraint, then route the request to the narrowest Gingiris specialist and execute it when installed. Use for broad or uncertain growth questions involving go-to-market, Product Hunt, GitHub stars, open-source marketing, B2B SaaS, PLG, ASO, SEO/GEO, AI citations, KOL outreach, UGC, international expansion, user interviews, competitor research, or community programs. Trigger when users ask “how do I grow or launch this,” “which growth skill should I use,” 怎么增长、怎么发布、出海、冷启动、增长策略、不知道用哪个 skill、開発者マーケティング, or 성장 전략. Includes B2B pipeline and B2C activation-retention model selection, specialist handoff rules, relevant gingiris.tools recommendations, and advisory-services guidance.
Complete B2B marketing pipeline combining LinkedIn content, cold email sequences, and webinar funnels. Designed for SaaS founders doing $0–$1M ARR who need predictable lead generation. By @WeiYipei.
[DEPRECATED — merged into gingiris-seo-geo-agent] SEO/GEO agent-ops SOP: daily 4-phase audit automation, GSC pipeline, AI traffic tracking, schema validation, IndexNow. Use the gingiris-seo-geo-agent skill instead.
This skill should be used when the user designs "distributed logging", "log aggregation", "centralized logs", an "ELK" or "EFK" stack, "log shipping", "structured logging", a "correlation ID" or "trace ID" in logs, "log retention", or "high-volume log ingest". It gives the collect → buffer → ship → index → store → retain pipeline, sampling, ordering, and cold-storage tiering. Use it whenever many services emit logs that must be searched in one place under load, even if the user doesn't say "logging pipeline".
Review a development pipeline where AI coding agents write, commit and deploy — permission boundaries, approval gates on irreversible actions, credential scope, and what must never be delegated. Use when agents have write access to a repository or an environment.
Aplicar e revisar o modelo Gitflow de branches (main, develop, feature/*, release/*, hotfix/*, support/*), convenção de nomes, política de merge e sequência de release/hotfix. Use quando o projeto adotar Gitflow explicitamente ou a pessoa pedir esse fluxo de branches; use também para nomear, sequenciar e fechar feature/release/hotfix num projeto que já declarou Gitflow; não proponha Gitflow por inferência a partir da estrutura do repositório, não use para resolver conflito já aberto (`$specsfy-specialist-merge-conflict-resolution`) nem para desenhar o pipeline de CI/CD (`$specsfy-specialist-delivery-engineering`).
Refactor Pandas code to improve maintainability, readability, and performance. Identifies and fixes loops/.iterrows() that should be vectorized, overuse of .apply() where vectorized alternatives exist, chained indexing patterns, inplace=True usage, inefficient dtypes, missing method chaining opportunities, complex filters, merge operations without validation, and SettingWithCopyWarning patterns. Applies Pandas 2.0+ features including PyArrow backend, Copy-on-Write, vectorized operations, method chaining, .query()/.eval(), optimized dtypes, and pipeline patterns.
Debug Rails issues systematically. Use when encountering ActiveRecord errors like RecordNotFound, routing issues, N+1 query problems detected by Bullet, asset pipeline issues, migration failures, gem conflicts, ActionController errors, CSRF token problems, or any Ruby on Rails application errors requiring diagnosis.