33 skills found · Page 1 of 2
openclaw / taskflowCoordinate multi-step detached tasks as one durable TaskFlow job with owner context, state, waits, and child tasks.
anthropics / MCP IntegrationThis skill should be used when the user asks to "add MCP server", "integrate MCP", "configure MCP in plugin", "use .mcp.json", "set up Model Context Protocol", "connect external service", mentions "${CLAUDE_PLUGIN_ROOT} with MCP", or discusses MCP server types (SSE, stdio, HTTP, WebSocket).
mksglu / context-modeContext window optimization for AI coding agents. Sandboxes tool output (98% reduction), persists session memory, and enforces routing across 17 platforms via MCP + hooks.
alexgreensh / token-optimizerFind the ghost tokens. Fix them. Survive compaction. Avoid context quality decay.
AgriciDaniel / wp-mcp-ultimateWordPress MCP Ultimate — Full MCP server with 58 WordPress abilities. Connect WordPress to any AI via Model Context Protocol.
kromahlusenii-ops / ham(HAM) Memory system for AI coding agents. Cut token usage by 80% by scoping context to directories.
faugustdev / git-context-controllerStructured context management framework for LLM agents. Implements Git-like operations (COMMIT, BRANCH, MERGE) to manage long-horizon agent memory.
massimodeluisa / recursive-decomposition-skillClaude Code skill for handling long-context tasks through recursive decomposition
Anjos2 / recursive-researchClaude Code skill for recursive research up to PhD level across any domain. Source tiering, WDM + Munger inversion for autonomous decisions, and disk checkpointing to survive context compaction.
kochetkov-ma / claude-brewcodeBrewcode - full-featured development platform for Claude Code: infinite focus tasks with automatic context handoff, prompt optimization, skill/agent creation, quorum code reviews, project rules management, and knowledge persistence
jnbno1163 / LG-token-saverSave 87% token usage for Claude Code. Zero install. 8 rules covering input+output+context. 6 months verified.
nocodework / ai-context-kitBuild a reusable Markdown context about you and your company (Claude Code skills + templates), then use it in ChatGPT, Claude, Gemini, Cursor or CLAUDE.md. Write context once, reuse everywhere. MIT.
woaillr-crypto / code2wikiAI Agent Skill — Auto-generate business context layer (BCL) for large backend codebases. Supports Java, Python, Go, Kotlin, TypeScript.
xenodium / d2This skill should be used when the user invokes "/d2" to create a diagram from the current context using D2 and output the resulting image path.
tody-agent / cm-continuityWorking memory protocol — maintains context across sessions via CONTINUITY.md. Inspired by Loki Mode. Read at turn start, update at turn end. Captures mistakes and learnings to prevent repeating errors.
agenvoy / search-suitable-public-apiSearch the curated Agenvoy public API list for an API that fits the current user need or skill context, then chain into the `api-tool-add` skill to register it under `~/.config/agenvoy/tools/api/`.
emanuelcasco / figmaAccess Figma design files using native pi tools — read LLM-ready summaries, explanations, implementation context, screenshots, components, styles, variables, and design tokens. Requires a Figma personal access token.
sageox / ox-consultThe hivemind for AI coding agents — persistent team context recorded once and recalled across agents, machines, and teammates.
sageox / ox-decisionThe hivemind for AI coding agents — persistent team context recorded once and recalled across agents, machines, and teammates.
sageox / ox-session-reviewThe hivemind for AI coding agents — persistent team context recorded once and recalled across agents, machines, and teammates.
amirkiarafiei / osp-query-agentOpen ScholarPeer is a Community Implementation of "ScholarPeer: A Context-Aware Multi-Agent Framework for Automated Peer Review" by Google DeepMind
amirkiarafiei / osp-answer-generator-agentOpen ScholarPeer is a Community Implementation of "ScholarPeer: A Context-Aware Multi-Agent Framework for Automated Peer Review" by Google DeepMind
Guilhem-Bonnet / godot-evidence-loopBoucle de preuve Godot via le serveur MCP Fennara : ancrer chaque claim sur des diagnostics éditeur, screenshots, contexte scène et logs runtime réels
sakamoto-family-smile / videodbSee, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips.
sarthkdobriyal / seo-project-setupSet up a durable local SEO workspace with project context, notes, goals, positioning, preferences, MCP checks, and Search Console data intake.
NeuralBlitz / practical-power-systems-synthesisThis skill enables synthesis in the domain of power-systems (engineering). It represents research-level-level expertise and is designed for production use in research, industry, and educational contexts. Use this skill when you need to perform synthesis operations related to power-systems.
NeuralBlitz / semi-supervised-optogenetics-testingThis skill enables testing in the domain of optogenetics (neuroscience). It represents intermediate-level expertise and is designed for production use in research, industry, and educational contexts. Use this skill when you need to perform testing operations related to optogenetics.
NeuralBlitz / data-mining-interpretation-fundamentalThis skill enables interpretation in the domain of data-mining (data-science). It represents fundamental-level expertise and is designed for production use in research, industry, and educational contexts. Use this skill when you need to perform interpretation operations related to data-mining.
NeuralBlitz / practical-classical-mechanics-simulationThis skill enables simulation in the domain of classical-mechanics (physics). It represents fundamental-level expertise and is designed for production use in research, industry, and educational contexts. Use this skill when you need to perform simulation operations related to classical-mechanics.
NeuralBlitz / infinite-recommender-systems-measurementThis skill enables measurement in the domain of recommender-systems (data-science). It represents intermediate-level expertise and is designed for production use in research, industry, and educational contexts.
