القائمة
جمع SkillsMP عدد ١٢٢ من skills من TheAdaply/re-forge. افتح أي skill لمراجعة مصدره وتفاصيله.
عرض ٤٠ من أصل ١٢٢ skills مجمعة.
Correlation-to-causation discipline for any "does X cause Y", "what is the effect of X", or "should we do X" question. Use when a decision rests on a causal claim drawn from observational data, an A/B test, an event study, or a regression with controls —…
لغة النص الأصلي: الإنجليزية
Provides guidance for interpreting and manipulating neural network internals using nnsight with optional NDIF remote execution. Use when needing to run interpretability experiments on massive models (70B+) without local GPU resources, or when working with any…
لغة النص الأصلي: الإنجليزية
Use this skill for long-horizon agentic coding where a feature spans many turns and the agent drifts: it freezes a re-readable contract before code. Writes EARS-style requirements -> design -> task breakdown -> verification evidence, one feature directory per…
لغة النص الأصلي: الإنجليزية
Build a backtest that will not lie to you — the engineering, not the statistics. Use when implementing, reviewing, or debugging a backtest/simulation of a trading or sequential-decision strategy: choosing event-driven vs vectorized, auditing…
لغة النص الأصلي: الإنجليزية
Run a Bayesian analysis as an ordered workflow, not a single fit: state and justify priors, prior-predictive-check before fitting, run the full Gelman-et-al workflow loop, gate on convergence diagnostics (R-hat, ESS, divergences), posterior-predictive-check…
لغة النص الأصلي: الإنجليزية
Data-quality engineering that runs BEFORE any analysis or model — even on one CSV. Use when ingesting, joining, transforming, caching, or reconciling data, or whenever a downstream number depends on a table being correct, fresh, and reproducible. Enforces…
لغة النص الأصلي: الإنجليزية
Structured red-teaming for any analysis, plan, or conclusion before it ships. Use when about to commit to a decision, recommend an approach, accept a result, or write a conclusion that others will act on — especially when the room agrees, the number looks…
لغة النص الأصلي: الإنجليزية
Risk thinking for portfolios and any decision under uncertainty. Use when sizing a bet, allocating capital, deploying a strategy, or making any irreversible call where a bad outcome can compound: ask the ruin question first (the bet size from which you cannot…
لغة النص الأصلي: الإنجليزية
Enforce hypothesis-testing discipline before you trust any p-value, win, or significance claim. Use when running an A/B test, comparing models or strategies, screening features, declaring a result 'significant', or deciding whether a null result means…
لغة النص الأصلي: الإنجليزية
Forecasting discipline for any time-ordered data — sensor logs, demand, prices, request rates, KPIs. Use when asked to forecast, predict the next value(s), model a series with a time index, test stationarity, decompose trend/seasonality, validate a forecast,…
لغة النص الأصلي: الإنجليزية
Run a tabular/ML competition end to end the way a grandmaster does: metric-first scoping, leakage forensics, a validation scheme that mirrors the test split before any model, a dumb baseline, one-change-per-experiment iteration, winner-derived…
لغة النص الأصلي: الإنجليزية
Procedures for competing in LLM-era ML competitions — NLP/text classification, LLM fine-tuning tracks, and prompt/agent contests. Use when the task is a text or LLM competition graded by a hidden metric under latency/memory caps: rebuild the metric locally…
لغة النص الأصلي: الإنجليزية
Interrogate any dataset the way a quantitative analyst does before trusting a single number from it — even a basic CSV. Use when asked to analyze, explore, model, backtest, or draw conclusions from data with a time dimension, a predictive target, many…
لغة النص الأصلي: الإنجليزية
Run re-forge teams as deterministic ultracode Workflow scripts in Claude Code: fan out one auditor per file/batch with adversarial refuters, gate behind a strict-schema synthesis agent. Use when the work is enumerable (audit N files, refute M claims) rather…
لغة النص الأصلي: الإنجليزية
Make a software project score the highest possible rating from an LLM evaluator (Claude Opus, GPT, code-review bots, preference models) AND from expert human reviewers — by building genuine, machine-verifiable quality and legibility, never by gaming judge…
لغة النص الأصلي: الإنجليزية
Write publication-ready ML/AI/Systems papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM, OSDI, NSDI, ASPLOS, SOSP. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX…
لغة النص الأصلي: الإنجليزية
Inventory the operator's workforce (agents, skills, plugins, installed MCP servers, recent research team SYNTHESIS files) and produce a ranked capability gap list. Diffs against VoltAgent's 10-category specialist taxonomy and wshobson/agents to find missing…
لغة النص الأصلي: الإنجليزية
Move a tested skill draft from ~/.claude/forge/drafts/ to ~/.claude/skills/<name>/ for personal use or to ~/.claude/forge/outputs/<plugin>/ for plugin packaging. Updates the Forge's MEMORY.md catalog with a bullet entry (authored_at, helpful_count=0,…
لغة النص الأصلي: الإنجليزية
Query external sources (MCP Registry, anthropics/skills, installed marketplaces) for candidate implementations of a specified capability. Applies the 6-rule trust heuristic to each candidate and returns ranked recommendations. Use when forge-gap has…
لغة النص الأصلي: الإنجليزية
Run the skill-creator eval loop against a forge-draft output to grade whether the drafted skill is promotable. Invokes the grader and analyzer agents plus the aggregate-benchmark script from the official skill-creator plugin and returns a pass/fail verdict +…
لغة النص الأصلي: الإنجليزية
Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction.…
لغة النص الأصلي: الإنجليزية
Simplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for DeepSpeed/FSDP/Megatron/DDP. Automatic device placement, mixed precision (FP16/BF16/FP8). Interactive config, single launch command. HuggingFace…
لغة النص الأصلي: الإنجليزية
PyTorch library for audio generation including text-to-music (MusicGen) and text-to-sound (AudioGen). Use when you need to generate music from text descriptions, create sound effects, or perform melody-conditioned music generation.
لغة النص الأصلي: الإنجليزية
Autonomous AI agent platform for building and deploying continuous agents. Use when creating visual workflow agents, deploying persistent autonomous agents, or building complex multi-step AI automation systems.
لغة النص الأصلي: الإنجليزية
Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support
لغة النص الأصلي: الإنجليزية
Quantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. Use when GPU memory is limited, need to fit larger models, or want faster inference. Supports INT8, NF4, FP4 formats, QLoRA training, and 8-bit optimizers. Works with…
لغة النص الأصلي: الإنجليزية
Vision-language pre-training framework bridging frozen image encoders and LLMs. Use when you need image captioning, visual question answering, image-text retrieval, or multimodal chat with state-of-the-art zero-shot performance.
لغة النص الأصلي: الإنجليزية
Guides researchers through structured ideation frameworks to discover high-impact research directions. Use when exploring new problem spaces, pivoting between projects, or seeking novel angles on existing work.
لغة النص الأصلي: الإنجليزية
Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or…
لغة النص الأصلي: الإنجليزية
OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning.…
لغة النص الأصلي: الإنجليزية
Anthropic's method for training harmless AI through self-improvement. Two-phase approach - supervised learning with self-critique/revision, then RLAIF (RL from AI Feedback). Use for safety alignment, reducing harmful outputs without human labels. Powers…
لغة النص الأصلي: الإنجليزية
Evaluates NVIDIA Cosmos Policy on LIBERO and RoboCasa simulation environments. Use when setting up cosmos-policy for robot manipulation evaluation, running headless GPU evaluations with EGL rendering, or profiling inference latency on cluster or local GPU…
لغة النص الأصلي: الإنجليزية
Applies cognitive science frameworks for creative thinking to CS and AI research ideation. Use when seeking genuinely novel research directions by leveraging combinatorial creativity, analogical reasoning, constraint manipulation, and other empirically…
لغة النص الأصلي: الإنجليزية
Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring…
لغة النص الأصلي: الإنجليزية
Expert guidance for distributed training with DeepSpeed - ZeRO optimization stages, pipeline parallelism, FP16/BF16/FP8, 1-bit Adam, sparse attention
لغة النص الأصلي: الإنجليزية
Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming
لغة النص الأصلي: الإنجليزية
Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure…
لغة النص الأصلي: الإنجليزية
Optimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Use when training/running transformers with long sequences (>512 tokens), encountering GPU memory issues with attention, or need faster inference. Supports…
لغة النص الأصلي: الإنجليزية
GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.
لغة النص الأصلي: الإنجليزية
Post-training 4-bit quantization for LLMs with minimal accuracy loss. Use for deploying large models (70B, 405B) on consumer GPUs, when you need 4× memory reduction with <2% perplexity degradation, or for faster inference (3-4× speedup) vs FP16. Integrates…
لغة النص الأصلي: الإنجليزية