A Korean-language prompt-writing toolkit for turning vague image requests into detailed prompts for GPT Image. It covers posters, covers, illustrations, promotional materials, typography, presentations, and related formats.
A skill for writing structured prompts for AI video generators such as Sora, Runway, and Veo. It focuses on videos that look like real recordings, including phone footage, home videos, documentary clips, and security-camera footage.
Process documents with Blockify API to create optimized IdeaBlocks for RAG. Search external ChromaDB knowledge bases with 100k+ blocks. Use when processing documentation, creating knowledge bases, improving AI context retrieval, or when user mentions Blockify, IdeaBlocks, or knowledge distillation.
Use for any task involving the tangermeme library — post-training analysis of genomic sequence-to-function (S2F) deep learning models. Triggers on predictions, DeepLIFT/SHAP attributions, marginalization/ablation/spacing of motifs, saturation mutagenesis (ISM), variant effect scoring, sequence design, seqlet calling…
Write and run custom Pi prompt templates (slash commands) for this extension. Use when creating templates with model selection, deterministic pre-steps, loops, chains, subagents, or best-of-N compare flows.
The pre-deployment gate for managed AI platforms (Azure AI Foundry, Google Vertex AI, AWS Bedrock), evals packed, budget set, guardrails on, owner named. Use before any cloud deployment.
Use when switching AI persona/language style. Syncs 13+ character profiles (Ding Yuanying, Lin Daiyu, Lu Xun, Li Yunlong, etc.) from GitHub, generates persona prompts with thinking patterns, rhetoric, and speech traits.
Build custom Python data sources for Apache Spark using the PySpark DataSource API — batch and streaming readers/writers for external systems. Use this skill whenever someone wants to connect Spark to an external system (database, API, message queue, custom protocol), build a Spark connector or plugin in Python…
Use when polishing, diagnosing, tailoring, or exporting resumes for LLM, RAG, Agent, Agentic RL, post-training, pretraining, AIGC, search/ranking, multimodal, AI backend, or LLM algorithm internships from raw resume text, a materials folder, and/or a target job description. Audits evidence, maps JD fit, enforces truth…
Train and evaluate a navigation policy in the habitat-gs simulator. Covers the full generate-episodes → train → evaluate flow for PointNav / ImageNav / ObjectNav (Habitat-Lab + DDPPO reinforcement learning) and for Vision-and-Language Navigation (StreamVLN, Uni-NaVid). Use when the user wants to train, fine-tune…
Audit and optimize Pisper system-prompt and tool-schema token overhead while preserving stable prompt-cache prefixes, permissions, and runtime behavior. Invoke only for explicit prompt or tool-context optimization work.
Route AI coding queries to local LLMs in air-gapped networks. Integrates Serena MCP for semantic code understanding. Use when working offline, with local models (Ollama, LM Studio, Jan, OpenWebUI), or in secure/closed environments. Triggers on local LLM, Ollama, LM Studio, Jan, air-gapped, offline AI, Serena, local…
This skill should be used when users want to fine-tune language models or perform reinforcement learning (SFT, DPO, GRPO, ORPO, KTO, SimPO) using the highly optimized Unsloth library. Covers environment setup, LoRA patching, VRAM optimization, vision/multimodal fine-tuning, TTS, embedding training, and…
Periodically measure the retrieval quality of the knowledge base using evaluateretrieval (MRR@5, Recall@5, Precision@5) plus getindexstats for health metrics. Run weekly, after significant reindex activity, or when the user reports declining answer quality. Prevents silent index rot and grounds "should we tune X"…
Inspect or show a local Codex task trajectory, including turns, approximate model steps, assistant messages, reasoning summaries, tool calls, failures, compaction, token usage, and timing. Use when the user asks for a trajectory, execution trace, task timeline, slow-tool analysis, visual event ledger, or live…
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Set up the Graphsignal Profiler for inference workloads — vLLM, SGLang, PyTorch, and dstack services. Use when the user wants GPU profiling, tracing, or monitoring for inference, asks about graphsignal-run or graphsignal.watch(), or asks about CUPTI / Prometheus / OTLP setup.
Expert in PerforatedAI library for adding artificial dendrites to PyTorch neural networks. Triggers: 'Perforate my model' (start interactive setup), 'debug my perforated model' (debug/optimize existing integration), 'load my perforated model for inference' (deploy trained models). Also use when: debugging dendrite…
Manages free AI models from OpenRouter for OpenClaw. Automatically ranks models by quality, configures fallbacks for rate-limit handling, and updates openclaw.json. Use when the user mentions free AI, OpenRouter, model switching, rate limits, or wants to reduce AI costs.
Plan and write a standard DataFlow pipeline from a target and representative JSONL data. Use when a user asks to select DataFlow operators, trace field dependencies, generate runnable pipeline code, or repair a pipeline with schema or field-flow errors.
Primary entrypoint for coding agents using CAIRA as reference material to design and build generative AI solutions with Azure AI Foundry, Azure OpenAI-compatible endpoints, agent frameworks, APIs, and frontends tailored to a user's scenario.
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: