14,252 mods in this category, of every kind an
agent can take. Each one carries what it costs per session, what the
scan found, and whether it is the original.
AI Agent-driven Kaggle competition workflow. Learn from real competition experience: score stabilization patterns, submission troubleshooting, kernel workflows, GPU task delegation, and the spec-driven development approach that achieved top leaderboard positions. Use when: working on any Kaggle competition, analyzing…
Translate between NLPCore and NARS through BrainClient/ModelMux while preserving an immutable Hermes transcript CID and its CoreNLP sentence/dependency record.
A locally running retrieval-augmented generation (RAG) service. RAG helps an AI find relevant information from a knowledge collection before answering.
MCP server "mcp-server-pixeltable-developer" as configured in pixeltable/mcp-server-pixeltable-developer. Runs locally from the mcp-server-pixeltable-developer Python package. Needs 2 environment variables to run.
Use Chutes.ai from Hermes for model discovery, routing, account/API-key guidance, and OpenAI-compatible inference. Prefer the live models endpoint for current availability and capabilities.
Process large volumes of requests using Gemini Batch API via scripts/. Use for batch processing, bulk text generation, processing JSONL files, async job execution, and cost-efficient high-volume AI tasks. Triggers on "batch processing", "bulk requests", "JSONL", "async job", "batch job".
Guard and improve prompts before expensive Codex, IDE, or CLI agent work. Use when a prompt is vague, broad, risky, costly, or should be optimized before implementation.
A team workflow for solving mathematical modelling problems with code, including analysis, model selection, computation, plots, and reproducibility notes.
Automatically refines every user prompt into a structured, actionable version, then immediately executes the optimized prompt. When triggered explicitly with "/optimize {prompt}", "optimize:", or "optimize prompt:", outputs the refined prompt as text instead.
Build AI agents with structured access to Sanity content via Sanity Context. Use when setting up a Sanity-powered chatbot, connecting an AI assistant to Sanity content, or adding client-side tools to an agent. Covers MCP endpoint setup in the Context app or with the Sanity CLI (GROQ mode over a dataset, or Knowledge…
Write, review, and optimize professional prompts for large language models. Use this skill whenever the user asks to write, draft, design, improve, fix, debug, review, or optimize a prompt, system prompt, prompt template, meta-prompt, or agent instructions; asks why a prompt "isn't working" or gives inconsistent…
Kedro deployment guidance for Databricks. Use when choosing between Git folders, Databricks Connect and Declarative Automation Bundles (DABs, formerly Databricks Asset Bundles), packaging a Kedro project as a wheel, generating or editing a bundle with kedro-databricks, getting conf and environments onto Databricks…
Multimodal RAG, video search, image similarity search, agent memory, and embeddings stored with your data. Tables, computed columns, vector search, and video, audio, image, and document pipelines.
★not rated 6
changed 6d agoA
tokens not measured
originalApache-2.0
MCP server "togetherai-image-server" as configured in stefanskiasan/togetherai-image-mcp-server. Runs locally from the togetherai-image-server npm package.
★not rated 6 1y agoA
tokens not measured
originalMIT
Maximize Claude's output quality while minimizing input token usage. Use this skill whenever a user wants to compress prompts, reduce token consumption, extract maximum output from Claude, write high-density instructions, optimize system prompts, or improve AI communication efficiency. Trigger on phrases like…
★not rated 6 5mo agoA134 tokens
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