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Found 2,037 Skills
Setup and workflow for using sqry semantic code search as an MCP server with Gemini CLI. Covers installation, MCP configuration via settings.json, context file behavior, and recommended patterns. Install this skill to give Gemini CLI access to sqry's 34 AST-based code analysis tools.
Phase-based development workflow manager that guides projects through structured phases from strategy and design through implementation, quality assurance, and launch. Manages roadmaps, feature branches, agent orchestration, and MCP server configuration.
Build applications where agents are first-class citizens. Use this skill when designing autonomous agents, creating MCP tools, implementing self-modifying systems, or building apps where features are outcomes achieved by agents operating in a loop.
Choose before `admin` when the user needs **Shopify CLI** to run or fix something now: validate app or extension config on disk (`shopify.app.toml`, `shopify.app.<name>.toml`, `shopify.extension.toml`) with **`shopify app config validate --json`** (not Admin GraphQL; MCP has no TOML validator); run or troubleshoot store workflows (`shopify store auth`, `shopify store execute`); inventory or product changes by handle, SKU, or location name; or CLI setup, auth, upgrade issues. Emphasize **commands and operational steps**, not only authoring GraphQL. Skip for API-only understanding or codegen with no CLI execution. Examples: validate before deploy; run an existing query via CLI; list products; missing `shopify store execute`.
Academic-first Draw.io figure skill for papers, theses, IEEE-style diagrams, architecture figures, workflows, roadmaps, formulas, and publication-ready visualizations. Use when users ask to draw, redraw, replicate, edit, or export diagrams for academic papers or technical documents. Creates offline .drawio + .spec.yaml + .arch.json bundles, exports SVG locally, uses draw.io Desktop CLI for embedded SVG/PNG/PDF/JPG, supports style presets, self-check review loops, and diagrams.net URL fallback without requiring MCP.
Authoritative reference for the neo4j-agent-memory Python package — a graph-native memory system for AI agents built on Neo4j — and for the hosted service (NAMS) at memory.neo4jlabs.com. Use this skill whenever the user mentions neo4j-agent-memory, agent memory with Neo4j, context graphs, the POLE+O model, MemoryClient/MemorySettings, the memory MCP server, or any of the framework integrations (LangChain, PydanticAI, CrewAI, AWS Strands, Google ADK, Microsoft Agent Framework, OpenAI Agents, LlamaIndex). Also use when the user mentions the hosted service at memory.neo4jlabs.com, NAMS, the Neo4j Agent Memory Service, the `nams_` API key prefix, or the hosted MCP endpoint. Also use when writing documentation, blog posts, tutorials, PRDs, or code samples for the project, when comparing agent memory approaches, or when positioning graph-native memory against vector-only approaches — even if the user doesn't explicitly name the package.
Error-to-fix playbook for every known failure mode on the OpenFinance backend — Polymarket, Relay, Hyperliquid, Privy delegation, and Solana RPC issues. Use this the moment a call fails, returns an unexpected status, or behaves inconsistently with on-chain state. Triggers on ANY of these error signatures verbatim or in paraphrase. Polymarket: "allowance: 0 but on-chain shows max", "CLOB reports allowance 0", "approvals confirmed but order rejected", "404 upstream" on market orders, "tick size" rejection, "order size below minimum", USDC.e vs pUSD vs native USDC confusion, V1 vs V2 exchange confusion. Relay: "InstructionFallbackNotFound", "Custom:101", "Custom:6000", "AnchorError", "Blockhash not found", "TransactionExpired", "No valid authorization signatures were provided", "Solana wallet is not delegated to the app", 412 delegation errors, quote succeeded but execute failed, stuck funds on Solana, stuck funds cross-chain, topupGas forced off. Hyperliquid: "Insufficient perp account value", "price out of bounds", WebSocket stale data, spot vs perp balance confusion. General: any "why is X failing", "why does on-chain and API state disagree", "what does this error mean". Read this BEFORE assuming a bug in the MCP or backend — most of these errors are already catalogued with known fixes.
Guides all better-i18n integration decisions — SDK selection (Next.js, React, Expo, Swift, Flutter, Remix), CDN vs GitHub workflow, AI-powered translation management via MCP tools, CLI health checks (scan, doctor, sync), Content CMS (localized models, entries, custom fields), file format conventions (flat / nested / namespaced), key naming, publish flows, and quality analytics. Use whenever building, modifying, or reviewing any localization feature — including i18n setup, adding languages, managing translation keys, publishing, or integrating AI workflows.
Buffett-style single-stock moat diagnostic — "Would Buffett buy this stock?" Five dimensions: business & moat / financial health / management & capital allocation / valuation & margin of safety / long-term visibility. Data from Longbridge CLI first, MCP fallback, WebSearch only for gaps. Runs cross-statement reconciliation (勾稽校验) BEFORE scoring; data-source appendix closes with a one-line reconciliation summary. Output: star-rated radar card, dimension detail, Buffett-voice narrative, mandatory holding-period education block. Triggers: "巴菲特", "护城河", "巴菲特会买吗", "价值投资", "好生意", "宽护城河", "定价权", "诊股", "巴菲特诊股", "巴菲特视角", "长期持有", "護城河", "巴菲特會買嗎", "價值投資", "寬護城河", "定價權", "診股", "巴菲特診股", "巴菲特視角", "長期持有", "Buffett", "Warren Buffett", "moat", "economic moat", "wide moat", "pricing power", "value investing", "owner earnings", "would Buffett buy", "Berkshire-style", "quality compounder".
Guide for using the Pinecone CLI (pc) to manage Pinecone resources from the terminal. The CLI supports ALL index types (standard, integrated, sparse) and all vector operations — unlike the MCP which only supports integrated indexes. Use for batch operations, vector management, backups, namespaces, CI/CD automation, and full control over Pinecone resources.
Generate 5–6 App Store screenshots in a given brand's aesthetic from a `brand.md`, raw product screenshots, or a public App Store listing fetched through Pika MCP. Story-driven (hook → value → features → proof → close), splashy, on-brand. Outputs 1290×2796 PNGs ready to drop into App Store Connect. Use when someone wants App Store / store listing assets — including: "make me app store screenshots", "design app store screens for [brand]", "I have a brand.md and screenshots, generate store assets", "screenshot set for app launch", "iOS store screens", "app store creative", "store listing visuals", "splashy app store screens", "app-store-screens".
Use this skill to manage Google Cloud Workload Manager evaluations, rules, scanned resources, and validation results by using public client libraries and the REST API. Use when you need to inspect workload best-practice rules, create and run evaluations for Google Cloud general best practices, SAP, SQL Server, or custom organizational rules, review violations, export results to BigQuery, or automate Workload Manager through client libraries because no service-specific public CLI or MCP server is available. Don't use for general Google Compute Engine instance management, VPC configuration, or standard IAM auditing.