Browse Skills — Page 165

literature-close-read

aipoch/medical-research-skills

Produce a structured close-reading report from a paper's full PDF-to-Markdown text (with `## Page XX` pagination and image references) when you need to systematically extract background, research questions, methods, results, limitations, and reproducible experimental details.

literature-experiment-extract

aipoch/medical-research-skills

Extract experimental models, experimental methods, and biomarker information from paper Markdown (typically produced by PDF-to-Markdown tools) when a user provides paper Markdown and needs a structured, evidence-backed summary (1 Markdown + 3 CSVs).

literature-extensive-read

aipoch/medical-research-skills

Rapidly skim and summarize academic papers (default:PDF-to-Markdown full text with `## Page XX` pagination and image references) and output a structured extensive-reading summary in Markdown when you need to quickly understand research questions, methods, key results, conclusions, and decide whether intensive reading is worthwhile.

literature-filtering

aipoch/medical-research-skills

Filter literature by publication year, journal, and predefined screening rules to produce inclusion/exclusion lists; use when conducting preliminary screening or systematic review screening to narrow the literature scope.

literature-management

aipoch/medical-research-skills

Import local literature into a managed library; trigger when you need offline deduplication, tagging, and a searchable index.

literature-review

affaan-m/ECC

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

literature-review-agent

Ar9av/PaperOrchestra

Step 3 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the literature search strategy from outline.json — discover candidate papers via web search, verify them through Semantic Scholar (Levenshtein > 70 fuzzy title match, temporal cutoff, dedup by paperId), cross-corroborate against Crossref + OpenAlex to flag hallucinated citations, build a BibTeX file, and draft Introduction + Related Work using ≥90% of the verified pool. Runs in parallel with the plotting-agent. TRIGGER when the orchestrator delegates Step 3 or when the user asks to "find citations for my paper", "draft the related work", or "build the bibliography".

literature-statistics

aipoch/medical-research-skills

Generate statistics for publication-year and journal distributions from local references or PDFs; use when you need standardized Year/Journal tables and a summary without any network access.

literature-survey

yogsoth-ai/de-anthropocentric-research-engine

Autonomous Literature Survey Campaign — 5 research paradigms (scoping, systematic, deep, narrative, snowball) with quantitative budget enforcement. Selects and executes the right survey paradigm based on research intent.

literatureimages-interpretation

aipoch/medical-research-skills

Interpret figures in academic papers and their captions when the input is a PDF-to-Markdown document with page markers and image links, producing a structured Markdown report for extracting variables, trends, and conclusions.

litigation-analysis

cat-xierluo/legal-skills

诉讼分析工具 - 判决书深度分析，生成上诉/再审决策支持

litreview

alirezarezvani/claude-skills

Academic literature orientation skill that searches papers via free keyless APIs (PubMed E-utilities + OpenAlex) by default — with the Consensus MCP as an optional enhancement lane when connected — builds a strategic search plan using PICO (default) or SPIDER / Decomposition / hybrid as fallbacks, and synthesizes findings into a formatted Word (.docx) research guide. Grill-me intake (research question specificity + framework hint + tentative depth) before the recon search; a second forcing checkpoint after Phase 2 confirms framework + sub-areas + depth before searches consume budget. Configurable depth (5/10/20 queries) controls coverage vs. speed. Output is a 'launching pad' — an orientation guide that lets a researcher dive in confidently, not a finished review. Use when the user starts literature-oriented research (e.g., 'litreview on [topic]', 'literature review on [topic]', 'I'm starting a literature review on X', 'I'm writing a paper on X', 'help me research X', 'I'm doing research on X', 'can you help me research X'). Do NOT use for single one-off paper searches wanting a quick list — that's a plain PubMed/OpenAlex (or Consensus) query.

Live Region Controller

Community-Access/accessibility-agents

Live region and dynamic content announcement specialist. Use when building or reviewing any feature that updates content without a full page reload including search results, filters, notifications, toasts, loading states, AJAX responses, form submission feedback, counters, timers, chat messages, progress indicators, or any content that changes after initial page load. Applies to any web framework or vanilla HTML/CSS/JS.

live_database_ingest

Kaelio/ktx

Capture semantic-layer and knowledge updates from a live database schema snapshot.

live-commerce

modu-ai/cowork-plugins

>

live-component

smnandre/symfony-ux-skills

Symfony UX LiveComponent for reactive server-rendered UI -- components that re-render via AJAX on user interaction, zero JavaScript required. Use when building live search, real-time filtering, dynamic forms, inline validation, dependent selects, auto-save, polling, deferred/lazy rendering, or any UI that updates itself based on user input. Code triggers: AsLiveComponent, LiveProp, LiveAction, data-model, data-loading, data-live-action-url, ComponentWithFormTrait, LiveListener, emit, defer, lazy, polling. Also trigger when the user asks "how to build a search that filters as I type", "how to validate a form in real-time", "how to make a reactive component in PHP", "how to build dependent selects", "how to defer component rendering", "how to communicate between components via emit", "how to bind a form to a LiveComponent". Do NOT trigger for static reusable UI without reactivity (use twig-component), pure client-side JS behavior (use stimulus), or page-level navigation (use turbo).

live-dashboard

indranilbanerjee/digital-marketing-pro

Create live Looker Studio dashboards. Use when: connecting marketing data sources with auto-configured visualizations.

live-preview

SethGammon/Citadel

>-

liveblocks

TerminalSkills/skills

Expert guidance for Liveblocks, the platform for adding real-time collaboration features to web applications. Helps developers implement live cursors, presence indicators, collaborative editing, comments, and notifications using Liveblocks' React hooks and APIs.

livekit

TerminalSkills/skills

>-

livekit-skills

fcakyon/claude-codex-settings

Build voice AI agents with LiveKit Agents SDK. Use when the user asks to "build a voice agent", "create a LiveKit agent", "add voice AI", "implement handoffs", "structure agent workflows", or is working with LiveKit Agents SDK. Covers both LiveKit Cloud and self-hosted deployments using lk CLI.

livesession-automation

ComposioHQ/awesome-claude-skills

"Automate Livesession tasks via Rube MCP (Composio). Always search tools first for current schemas."

liveview-code-review

existential-birds/beagle

Reviews Phoenix LiveView code for lifecycle patterns, assigns/streams usage, components, and security. Use when reviewing LiveView modules, .heex templates, or LiveComponents.

liveview-patterns

oliver-kriska/claude-elixir-phoenix

Build LiveView: async data (assign_async), PubSub (check connected?), phx-change events, form components/modals/uploads, streams for lists, live_patch. Use when handling interactions, debugging events, or tracking Presence.

lksg-csddd-lieferkettensorgfalt

Klotzkette/claude-fuer-deutsches-recht

Unternehmen ab 1000 Mitarbeitern muss Lieferketten-Sorgfaltspflichten nach LkSG und kuenftig CSDDD erfuellen. LkSG seit 1.1.2023 CSDDD Richtlinie 2024/1760 Phasing ab 2027. Normen LkSG §§ 3 4 8 11 24 CSDDD Art. 1 ff. Pruefraster Anwendungsbereich Sorgfaltspflichten Risikoanalyse Beschwerdemechanismus BAFA-Aufsicht. Output Risikoanalyse-Template Grundsatzerklaerung Beschwerdeverfahren. Abgrenzung zu esg-greenwashing-csrd (Berichtspflicht) und umweltrecht-transaktionen-dd (M&A).

llama-cpp

NousResearch/hermes-agent

llama.cpp local GGUF inference + HF Hub model discovery.

llama-factory

Orchestra-Research/AI-Research-SKILLs

Expert guidance for fine-tuning LLMs with LLaMA-Factory - WebUI no-code, 100+ models, 2/3/4/5/6/8-bit QLoRA, multimodal support

llamacloud-index

run-llama/llamaparse-agent-skills

Use this skill whenever a question should be answered from documents stored in a LlamaCloud Index v2 knowledge base — retrieving passages, locating indexed files, or searching indexed content through the LlamaParse Platform REST API with curl. Teaches agentic retrieval — navigating an index like a file system instead of one-shot RAG.

llamactl-qa

run-llama/llama-agents

Plan and run a design-QA / "taste test" of llamactl changes against a real backend. Cooperatively builds a small matrix of cases worth eyeballing, runs them against a chosen backend (test environment by default, local kind+tilt for new API contract changes), and writes a design-review report to `thoughts/shared/qa/`. Use this for changes to `llamactl` commands, output formats, auth, or control-plane API contracts. For UI/template smoke tests, use `llamactl_browser_test` instead.

llamafile

TerminalSkills/skills

Expert guidance for llamafile, the tool that packages LLMs into single executable files that run on any OS (Linux, macOS, Windows, FreeBSD) without installation. Helps developers create portable AI applications, run models offline, and distribute LLMs as self-contained binaries with built-in web UI and OpenAI-compatible API.

llamaguard

Orchestra-Research/AI-Research-SKILLs

Meta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons, substances, self-harm, criminal planning. 94-95% accuracy. Deploy with vLLM, HuggingFace, Sagemaker. Integrates with NeMo Guardrails.

llamaindex

Orchestra-Research/AI-Research-SKILLs

Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval, or building RAG pipelines. Best for data-centric LLM applications.

llamaparse

run-llama/llamaparse-agent-skills

Use this skill when the user asks to parse the content of an unstructured file (PDF, PPTX, DOCX...)

llamaparse-mcp

run-llama/llamaparse-agent-plugins

Skill on how to use the LlamaParse MCP tools

llava

NousResearch/hermes-agent

Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.

lld-reviewer

TestAny-io/testany-agent-skills

LLD review, Low-Level Design review, 详细设计评审。Use when: 实现前需要审查 LLD 与 PRD/HLD/API Contract/Guardrails 的一致性。

lld-writer

TestAny-io/testany-agent-skills

Write LLD, Low-Level Design, 写详细设计。Use when: PRD/HLD/API Contract 完成后需要写模块设计、接口设计、实现级技术方案。

llm-ai-hunter

H-mmer/pentest-agents

LLM and Agentic AI vulnerability specialist. Covers OWASP LLM Top 10 v2025 (LLM01-LLM10) and OWASP Agentic AI Top 10 (AA-01..AA-10). Dispatcher passes subtype — 'prompt-injection', 'indirect-injection', 'tool-abuse', 'rag-poisoning', 'vector-idor', 'mcp', 'model-server', 'output-handling', or 'ascii-smuggling' — in the task; falls back to inference. Use when a target ships a chatbot, RAG / search-over-docs, AI assistant, MCP server, agentic tool-use plugin, model registry, inference server, or any 'AI feature' that processes attacker-influenceable text or files.

llm-app-patterns

tranhieutt/software_development_department

Provides architectural patterns for LLM-powered applications and AI assistants, including prompt engineering, RAG, agent loops, conversation management, and evaluation. Use when building AI-based features, chatbots, or complex AI system architectures.

llm-app-patterns-v2

diegosouzapw/awesome-omni-skills

\ud83e\udd16 LLM Application Patterns workflow skill. Use this skill when the user needs Production-ready patterns for building LLM applications, inspired by Dify and industry best practices and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

llm-app-patterns-v3

diegosouzapw/awesome-omni-skills

\ud83e\udd16 LLM Application Patterns workflow skill. Use this skill when the user needs Production-ready patterns for building LLM applications, inspired by Dify and industry best practices and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

llm-application-dev

MoizIbnYousaf/Ai-Agent-Skills

Building applications with Large Language Models - prompt engineering, RAG patterns, and LLM integration. Use for AI-powered features, chatbots, or LLM-based automation.

llm-application-dev-ai-assistant

benjaminasterA/antigravity-awesome-skills

You are an AI assistant development expert specializing in creating intelligent conversational interfaces, chatbots, and AI-powered applications. Design comprehensive AI assistant solutions with natur

llm-application-dev-ai-assistant-v2

diegosouzapw/awesome-omni-skills

AI Assistant Development workflow skill. Use this skill when the user needs You are an AI assistant development expert specializing in creating intelligent conversational interfaces, chatbots, and AI-powered applications. Design comprehensive AI assistant solutions with natur and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

llm-application-dev-langchain-agent

benjaminasterA/antigravity-awesome-skills

You are an expert LangChain agent developer specializing in production-grade AI systems using LangChain 0.1+ and LangGraph.

llm-application-dev-langchain-agent-v2

diegosouzapw/awesome-omni-skills

LangChain/LangGraph Agent Development Expert workflow skill. Use this skill when the user needs You are an expert LangChain agent developer specializing in production-grade AI systems using LangChain 0.1+ and LangGraph and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

llm-application-dev-prompt-optimize

benjaminasterA/antigravity-awesome-skills

You are an expert prompt engineer specializing in crafting effective prompts for LLMs through advanced techniques including constitutional AI, chain-of-thought reasoning, and model-specific optimizati

llm-application-dev-prompt-optimize-v2

diegosouzapw/awesome-omni-skills

Prompt Optimization workflow skill. Use this skill when the user needs You are an expert prompt engineer specializing in crafting effective prompts for LLMs through advanced techniques including constitutional AI, chain-of-thought reasoning, and model-specific optimizati and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

llm-artifacts-detection

existential-birds/beagle

Detects common LLM coding agent artifacts in codebases. Identifies test quality issues, dead code, over-abstraction, and verbose LLM style patterns. Use when cleaning up AI-generated code or reviewing for agent-introduced cruft.

llm-as-computer

oaustegard/claude-skills

Execute programs on a compiled transformer stack machine where every instruction fetch and memory read is a parabolic attention head. Demonstrates that transformer attention + FF layers can implement a working computer. Use when user mentions "llm-as-computer", "lac", "stack machine", "compiled transformer", "percepta", "parabolic attention", "execute program", or asks to run/trace programs on the transformer executor.

llm-benchmark

KerberosClaw/kc_ai_skills

Use when the user wants to test, compare, or choose local Ollama models for their machine. Checks Ollama/GPU state, recommends model sizes from available VRAM, preserves existing benchmark records, pulls only approved models, runs repeatable benchmarks, restores stopped services, and writes a markdown comparison report. NOT for hosted API model evaluation or subjective chat-quality judging without local benchmark commands.

llm-cost-optimizer

alirezarezvani/claude-skills

Use proactively whenever LLM API costs come up -- or should. Triggers include: 'my AI costs are too high', 'optimize token usage', 'which model should I use', 'LLM spend is out of control', 'implement prompt caching', 'we're about to launch an AI feature', 'build me an AI endpoint'. Don't wait for an explicit cost complaint -- if someone is building an AI feature, designing an LLM endpoint, or choosing between models, cost architecture belongs in the conversation. Apply immediately when any of these are true: a system prompt appears that exceeds a few hundred tokens, all requests are hitting the same model, max_tokens is not set, or no per-feature cost logging exists. NOT for RAG pipeline design (use rag-architect). NOT for improving prompt quality or effectiveness (use senior-prompt-engineer).

llm-council

rohitg00/pro-workflow

Provider-agnostic multi-LLM deliberation. Three phases — independent responses, cross-model anonymized ranking, chairman synthesis. Provider config from env (OPENAI/ANTHROPIC/FIREWORKS/OPENROUTER/custom OpenAI-compatible base URL). Persists transcript to a wiki page when --wiki <slug> is passed. Use when the user wants multiple AI perspectives, consensus-building, or the "LLM Council" approach for high-stakes reviews, plan critique, or contested learning rules.

llm-data-automation

datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction

Automate construction data processing using LLM (ChatGPT, Claude, LLaMA). Generate Python/Pandas scripts, extract data from documents, and create automated pipelines without deep programming knowledge.

llm-document-extraction

datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction

Extract structured data from construction documents using LLMs. Process RFIs, submittals, contracts, specifications. Convert unstructured PDFs to structured JSON/Excel.

llm-evaluation

benjaminasterA/antigravity-awesome-skills

Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or ...

llm-evaluation

wshobson/agents

Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.

llm-evaluation-v2

diegosouzapw/awesome-omni-skills

LLM Evaluation workflow skill. Use this skill when the user needs Master comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B testing and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

llm-friendly-context

shinpr/ai-coding-project-boilerplate

Clarifies inputs, outputs, success criteria, decisions, and unresolved conditions so downstream agents can execute without guessing. Use when writing or revising LLM-facing prompts, handoffs, planning artifacts, reviews, reports, or generated instructions.

llm-gate

rohitg00/pro-workflow

LLM-powered quality verification using prompt hooks. Validates commit messages, code patterns, and conventions using AI before allowing operations. Use to set up intelligent guardrails.

llm-icon-finder

daymade/claude-code-skills

Finding and accessing AI/LLM model brand icons from lobe-icons library. Use when users need icon URLs, want to download brand logos for AI models/providers/applications (Claude, GPT, Gemini, etc.), or request icons in SVG/PNG/WEBP formats.

llm-integration

yonatangross/orchestkit

LLM integration patterns for function calling, streaming responses, local inference with Ollama, and fine-tuning customization. Use when implementing tool use, SSE streaming, local model deployment, LoRA/QLoRA fine-tuning, or multi-provider LLM APIs.

llm-judge

existential-birds/beagle

Use when comparing two or more code implementations against a spec or requirements doc. Triggers on \"which repo is better\", \"compare these implementations\", \"evaluate both solutions\", \"rank these codebases\", or \"judge which approach wins\". Also covers choosing between competing PRs or vendor submissions solving the same problem. Does NOT review a single codebase for quality \u2014 use code review skills instead. Does NOT evaluate strategy docs \u2014 use strategy-review. Requires a spec file and 2+ repo paths.

llm-models

inferen-sh/superpowers

Access Claude, Gemini, Kimi, GLM and 100+ LLMs via inference.sh CLI using OpenRouter. Models: Claude Opus 4.5, Claude Sonnet 4.5, Claude Haiku 4.5, Gemini 3 Pro, Kimi K2, GLM-4.6, Intellect 3. One API for all models with automatic fallback and cost optimization. Use for: AI assistants, code generation, reasoning, agents, chat, content generation. Triggers: claude api, openrouter, llm api, claude sonnet, claude opus, gemini api, kimi, language model, gpt alternative, anthropic api, ai model api, llm access, chat api, claude alternative, openai alternative

llm-ops

diegosouzapw/awesome-omni-skills

LLM-OPS -- IA de Producao workflow skill. Use this skill when the user needs LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

llm-ops-v2

diegosouzapw/awesome-omni-skills

LLM-OPS -- IA de Producao workflow skill. Use this skill when the user needs LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

llm-optimized-content

guia-matthieu/clawfu-skills

Use when creating content that must be discoverable by AI search engines (ChatGPT, Perplexity, Gemini). Use when SEO alone isn't enough, when you need AI citations, or when optimizing for the "zero-click" future.

llm-patterns

alinaqi/maggy

AI-first application patterns, LLM testing, prompt management

llm-prompt-optimizer

diegosouzapw/awesome-omni-skills

LLM Prompt Optimizer workflow skill. Use this skill when the user needs improving prompts for any LLM. Applies proven prompt engineering techniques to boost output quality, reduce hallucinations, and cut token usage and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

llm-prompt-optimizer-v2

diegosouzapw/awesome-omni-skills

LLM Prompt Optimizer workflow skill. Use this skill when the user needs improving prompts for any LLM. Applies proven prompt engineering techniques to boost output quality, reduce hallucinations, and cut token usage and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

llm-runtime-architecture

agentlas-ai/Agentlas-OS

Use when designing how one canonical agent core runs across Codex, Claude Code, Gemini CLI, Cursor, and AGENTS.md-compatible tools.

llm-seo-readiness

aptos-labs/aptos-docs

>-

llm-structured-output

diegosouzapw/awesome-omni-skills

LLM Structured Output workflow skill. Use this skill when the user needs > and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

llm-structured-output-v2

diegosouzapw/awesome-omni-skills

LLM Structured Output workflow skill. Use this skill when the user needs > and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

llm-trading-agent-security

affaan-m/ECC

Security patterns for autonomous trading agents with wallet or transaction authority. Covers prompt injection, spend limits, pre-send simulation, circuit breakers, MEV protection, and key handling.

llm-wiki

NousResearch/hermes-agent

Karpathy's LLM Wiki: build/query interlinked markdown KB.

llm-wiki-lint

KerberosClaw/kc_ai_skills

Use when the user wants to lint a repo following the Karpathy LLM Wiki pattern (raw/ + wiki/ + SCHEMA.md / index.md / log.md). The skill detects path, scans wiki pages + schema layer, reports frontmatter gaps, broken in-body links, source traceability breaks, stale claims, orphan pages, index synopsis contradictions, and SCHEMA-vs-reality drift. Phase 1 is read-only report; Phase 2 (fix + log.md LINT entry) only runs after the user explicitly approves.

llm-wiki-setup

daymade/claude-code-skills

Co-create a personal investment-research LLM Wiki (Andrej Karpathy's pattern) where the user's OWN analysis framework becomes a living CLAUDE.md — by interviewing them, NOT by handing them a template. Use whenever the user wants to build a compounding research knowledge base, 投研第二大脑, 投研知识库, or 个人投研 wiki; instantiate Karpathy's LLM Wiki gist for finance/investing; turn their stock-picking, analyst-tracking, or earnings-watching workflow into a structured markdown vault; or build a wiki tracking companies / industries / macro / analysts over time. Pure markdown + wikilinks, NO RAG / vector DB (Karpathy's core idea — do not over-engineer). Also triggers for ingesting research reports / earnings calls / expert notes into an existing wiki, and for post-earnings prediction→fulfillment reviews. Core value = extracting the user's personal investment preferences into THEIR OWN schema, never imposing a standard one.

llms-txt

thatrebeccarae/claude-marketing

Generate and maintain llms.txt files for AI discoverability. Scans repos to create curated content maps that help AI answer engines surface your project accurately. Implements the llms.txt specification from Answer.AI.

llms-txt-generator

Varnan-Tech/opendirectory

Generates and maintains a standards-compliant llms.txt file for any website — either by crawling the live site OR by reading the website's codebase directly. Use this skill when asked to create an llms.txt, add AI discoverability to a site, improve GEO (Generative Engine Optimization), make a website readable by AI agents, generate an llms-full.txt, check if a site has llms.txt, or audit a site's AI readiness for generative search. Trigger this skill any time a user mentions llms.txt, AI discoverability, LLM site readability, or wants their site to appear in AI-generated answers. Also trigger when the user is inside a website codebase and asks about SEO, AI readiness, or content structure.

lm-evaluation-harness

mkurman/zorai

LLM evaluation framework (EleutherAI lm-evaluation-harness). Unified benchmark evaluation for language models with 200+ tasks, support for HuggingFace transformers, vLLM, SGLang, OpenAI API, GGUF, and custom models. Used by HuggingFace Open LLM Leaderboard. Covers MMLU, HellaSwag, ARC, GSM8K, HumanEval, BBH, TruthfulQA, and more.

lm-studio-subagents

TerminalSkills/skills

>-

lmnt-automation

ComposioHQ/awesome-claude-skills

"Automate Lmnt tasks via Rube MCP (Composio). Always search tools first for current schemas."

ln-11-plan-reviewer

levnikolaevich/claude-code-skills

Reviews implementation plans against repository evidence and current authoritative guidance. Use before execution to expose gaps and risks; not for completed delivery review.

ln-12-delivery-reviewer

levnikolaevich/claude-code-skills

Reviews a completed scoped change and its affected runtime and contract paths. Use to find change-caused defects and verify readiness; not for codebase audit, implementation, or repair.

ln-21-documentation-auditor

levnikolaevich/claude-code-skills

Audits documentation and code comments for structure, coverage, factual accuracy, and maintainability. Use for documentation trust reviews; not code, test, or architecture audits.

ln-22-codebase-auditor

levnikolaevich/claude-code-skills

Audits cross-cutting code health across security, delivery, maintainability, dependencies, diagnosability, concurrency, and lifecycle. Use when no specialist audit is primary.

ln-23-test-suite-auditor

levnikolaevich/claude-code-skills

Audits whether an existing test suite proves important product behavior with strong, isolated tests. Use when test confidence is uncertain; not to design or implement new tests.

ln-24-architecture-auditor

levnikolaevich/claude-code-skills

Audits implemented architecture fitness, boundaries, contracts, dependency topology, structure, and configuration ownership. Use for system structure; not implementation-plan review.

ln-25-persistence-auditor

levnikolaevich/claude-code-skills

Audits queries, transactions, data-path performance, and persistence resource lifecycle. Use when data correctness or scalability is at risk; not for general performance tuning.

ln-31-performance-optimizer

levnikolaevich/claude-code-skills

Optimizes a measured latency, throughput, memory, CPU, or I/O problem through profiling and keep-or-discard experiments. Use for a known bottleneck; not unbiased A/B comparison.

ln-32-dependency-upgrader

levnikolaevich/claude-code-skills

Upgrades dependencies across package managers with breaking-change research and rollback-safe verification. Use for dependency maintenance; not general code modernization.

ln-33-code-modernizer

levnikolaevich/claude-code-skills

Modernizes a bounded capability by removing obsolete custom mechanisms or reducing bundle and maintenance cost. Use for proven modernization value; not routine upgrades or tuning.

ln-34-benchmark-comparator

levnikolaevich/claude-code-skills

Compares tools or implementations through reproducible A/B workloads, correctness oracles, and controlled measurements. Use to choose alternatives; not to optimize a known bottleneck.

ln-41-test-strategy-planner

levnikolaevich/claude-code-skills

Designs a risk-based test strategy and prioritized scenarios without changing code. Use when requirements need a test plan; not for auditing or implementing tests.

ln-42-acceptance-test-builder

levnikolaevich/claude-code-skills

Creates and runs reproducible acceptance tests for stated requirements using project-native tooling. Use when executable acceptance evidence is needed; not for audits or product fixes.

ln-51-opportunity-evaluator

levnikolaevich/claude-code-skills

Evaluates new product directions using current demand, acquisition, competition, economics, and validation evidence. Use before commitment; not for backlog or implementation planning.

ln-61-skill-reviewer

levnikolaevich/claude-code-skills

Reviews standalone skills and their configured distribution surfaces before publication. Use for skill release readiness; not for product code or implementation-plan review.

ln-62-repository-publisher

levnikolaevich/claude-code-skills

Validates, commits, pushes, and remotely verifies approved repository changes. Use when publication is requested; not for releases, package publishing, or announcements.

ln-63-release-publisher

levnikolaevich/claude-code-skills

Prepares and publishes a tagged GitHub release from repository evidence. Use for an explicit release request; not for ordinary commits, packages, or community news.