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Found 1,886 Skills
Save 123RF stock photos and vectors without watermarks in original quality
Scaffolds a personal LLM Wiki from scratch — the Karpathy pattern of incrementally building a persistent, interlinked markdown knowledge base maintained by LLMs. Generates directory structure, schema file, index, log, and workflow conventions. Use when user says "create wiki", "new wiki", "bootstrap wiki", "llm wiki", "knowledge base", "start a wiki", "build a wiki", or wants to set up a structured markdown knowledge base for any domain.
Guides implementation of agent memory systems, compares production frameworks (Mem0, Zep/Graphiti, Letta, LangMem, Cognee), and designs persistence architectures for cross-session knowledge retention. Use when the user asks to "implement agent memory", "persist state across sessions", "build knowledge graph for agents", "track entities over time", "add long-term memory", "choose a memory framework", or mentions temporal knowledge graphs, vector stores, entity memory, adaptive memory, dynamic memory, or memory benchmarks (LoCoMo, LongMemEval). A core context engineering skill — also activates when the user mentions "context engineering" or "context-engineering" in the context of durable agent knowledge and cross-session persistence.
Generate pixel art diagrams and infographics in retro 16-bit SNES aesthetic — recovery education visuals, flowcharts, data visualizations, process diagrams with dithering and limited palettes. NOT for photo-realistic images, vector graphics, or high-resolution illustration.
OpenTelemetry with Grafana stack. Covers OTel SDK instrumentation for Go/Java/Python/Node.js/.NET, OTLP protocol and endpoint configuration, sending telemetry to Grafana Cloud via OTLP endpoint, Grafana Alloy as OTel collector, sampling strategies, Kubernetes OTel Operator, and migration from other observability tools. Use when instrumenting apps with OTel, configuring OTLP endpoints, setting up collectors, or migrating to OpenTelemetry.
Lovrabet Runtime CLI — Manage application directories, dataset queries, data CRUD, SQL execution, and BFF invocations via the lovrabet command. Trigger words: Cloud Diagram, lovrabet, lovrabet-cli, app list, dataset, data filter, data getOne, create, update, delete, sql exec, bff exec, accessKey, compress, jq.
Indie Hackers platform help — the largest founder community for bootstrapped and indie businesses (~1-2M monthly visits, 165K+ entrepreneurs). Covers community engagement strategy (post types, formatting, timing), product pages (revenue milestones, transparent metrics), groups, interviews, podcast, Partner Up co-founder matching, advertising, and IH+ premium. DR75 nofollow backlinks. Use when your Indie Hackers posts aren't getting traction, product page isn't attracting interest, want more visibility among bootstrapped founders, or unsure if IH is worth the time for your launch. Do NOT use for multi-directory launch coordination (use /sales-launch-directory). Do NOT use for other launch platforms (use the platform-specific skill).
Comprehensive ATS resume optimization for any field. Interview-driven resume building, rewriting existing resumes to fix ATS flags, scoring, and JD keyword tuning. Works for engineering, product, marketing, design, sales, finance, data, healthcare, legal, operations, HR, education, nonprofit, and government roles. Synthesizes 2026 best practices from Jobscan, Resume Worded, Enhancv, Harvard OCS, Indeed, LinkedIn Talent, Workday, Greenhouse. Triggers on: resume, CV, ATS, applicant tracking system, Jobscan, Resume Worded, Enhancv, TopResume, resume score, resume review, resume rewrite, resume builder, make my resume pass ATS, fix my resume, tailor to JD, quantify bullets, fix passive voice, action-verb repetition, non-standard job title, vague bullet, parse rate, keyword match, 1-page resume, 2-page resume, Staff / Principal / Lead / Senior / Director / Manager / VP / PM / designer / marketer / analyst / nurse / paralegal / etc.
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.
Novel content polishing and optimization, suitable for user requests such as "Help me polish this novel", "Improve the writing style", "Optimize chapter rhythm", "Enhance this highlight", "Make dialogues more natural", "Make this passage more engaging", "Optimize novel writing style", "Adjust chapter rhythm", "Make dialogues more realistic", "Help me revise this content", "Polish novel", "Optimize highlights", "Improve writing style", "Make this passage more immersive", etc. It provides 3 levels of polishing, focusing on optimization of writing style and content, supporting special optimizations such as style adaptation, rhythm tightening, highlight enhancement, dialogue optimization, etc. **Polished results directly modify the chapters/ directory, and automatic backups are made to .sumeru/write/original/ before modification**. **Sub-Agents are used for parallel processing during batch polishing, with each Agent responsible for a maximum of 3 chapters**
Industry valuation comparison and distribution analysis via Longbridge — cross-peer valuation matrix (PE / PB / PS / dividend yield), industry-percentile ranking, and industry premium / discount for a single stock. Triggers: "行业估值", "行业溢价", "行业折价", "行业对比", "行业百分位", "同行业估值", "板块估值", "行业贵不贵", "行業估值", "行業溢價", "行業折價", "行業對比", "行業百分位", "板塊估值", "industry valuation", "sector valuation", "industry premium", "industry percentile", "peer valuation", "sector PE", "TSLA.US industry valuation", "700.HK sector comparison".
Audit a directory of multilingual blog content for completeness, consistency, hreflang correctness, meta-tag parity, and freshness. Builds a translation coverage matrix, flags stale translations, validates hreflang and schema, and emits a prioritized report with runnable fix commands. Use when user says "locale audit", "blog locale-audit", "check translations", "multilingual audit", "translation check", "hreflang check", "Uebersetzungen pruefen".