13,728 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.
Transform any GitHub repository into searchable vector embeddings. MCP server with smart indexing, voyage-context-3 embeddings, and semantic search for Claude/Cursor IDEs. Runs locally from the embedocs-mcp npm package.
★not rated 7 1y agoA
tokens not measured
originalMIT
MCP server + proxy that cuts cloud LLM costs 36-42% by indexing context locally with Ollama and giving agents precision retrieval tools instead of raw dumps. Runs locally from the context-guardian-mcp npm package.
★not rated 7 5mo agoA
tokens not measured
originalMIT
Compile a natural-language spec into a tiny neural function that runs locally - classification, extraction, format repair, fuzzy matching, log triage, and routing.
★not rated 7▲
+1 2mo agoA
tokens not measured
originalMIT
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…
ES|QL expert agent — writes, debugs, and explains Elasticsearch Query Language (ES|QL) queries. Use when the user needs help writing ES|QL queries, understanding ES|QL syntax, debugging query errors, or exploring Elasticsearch data with ES|QL. Examples: top-N aggregations, null field debugging, index joins, Query DSL…
Translate between NLPCore and NARS through BrainClient/ModelMux while preserving an immutable Hermes transcript CID and its CoreNLP sentence/dependency record.
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.
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 Studio setup, agent implementation, and advanced patterns. Always use this skill when users mention…
★not rated 7▲
+3 todayA✓ AI reviewSocket: passSnyk: warn127 tokens
Analyze and improve existing Ozor.ai video prompts for better output quality. Use this skill whenever the user has an Ozor prompt that produced mediocre results, wants to improve a video prompt, needs help debugging why a video didn't turn out well, or wants expert feedback on their prompt before running it. Trigger…
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…
Operate and evaluate Unified AI System through twelve governed MCP tools, including provider-free prompt enhancement, while preserving fake-provider, authorization, and evidence boundaries.
Cut your AI bill without losing accuracy. tunelab helps you move repetitive LLM work — classifying, routing, extracting, drafting — onto small models that run for free on your Mac. It decides by experiment (testing on your own data first), trains locally with MLX, evaluates honestly, and explains every step so you…
★not rated 6 1mo agoA
tokens not measured
originalMIT
Transform vague prompts into precise, verifiable structured XML prompts that coding agents execute reliably. Modes: execute (default — generate then run) and plan (generate XML for review first). Use when the user says improve prompt, make this work better, prompt engineer, structure a request, plan a complex change…
Agent skills for building, deploying, evaluating, and monitoring LLM pipelines on the orq.ai platform.
★not rated 6
changed 8d agoA
tokens not measured
originalMIT
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: