181 skills · sorted by relevance
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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Use when a hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
The English summary is being prepared. Showing the original description.
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
The English summary is being prepared. Showing the original description.
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
The English summary is being prepared. Showing the original description.
Build, update, and query a persistent project knowledge graph from skills, memory, docs, and code structure — stdlib Python only, no external tools. Dual-mode: skill-library (agent-loom) or application (any consumer repo). Load when the user asks for a knowledge graph, project map, skill relationships, query the graph, update the graph, or trace how components connect. Auto-runs on memory-handoff and project-setup bootstrap. Also triggers on "build the graph", "what connects to X", "map this project".
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A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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Design bounded applications and workflows for an always-on AI agent with episodic memory. Covers product ideas, persistence-dependent workflows, and constructed examples that make delegation, interruption, evidence, and opt-out explicit. Activate on: "what can an always-on agent do", "persistent agent use cases", "agent applications", "proactive agent ideas", "what to build with episodic memory", "always-on agent product", "personal AI assistant ideas", "/always-on-agent-applications". NOT for: building the architecture (use always-on-agent-architecture), designing inputs (use always-on-agent-inputs), safety and privacy (use always-on-agent-safety).
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A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
The English summary is being prepared. Showing the original description.
Tracks complex, multi-session work using the Beads issue tracker and dependency graphs, and provides persistent memory that survives conversation compaction. Use when work spans multiple sessions, has complex dependencies, or needs persistent context across compaction cycles. Trigger with phrases like "create task for", "what's ready to work on", "show task", "track this work", "what's blocking", or "update status".
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Persistent AI companion with long-term memory, project context awareness, and multi-session continuity across any LLM.
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A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
The English summary is being prepared. Showing the original description.
Keep project context across Claude Code sessions by saving progress, decisions, blockers, and next steps. Commands retrieve project briefings, while a session-start hook loads a compact summary to help resume previous work.
Create engineering retrospectives from Git history, covering delivered changes, work patterns, test code ratios, and frequently changed files. Review individual contributions and improvement opportunities, save metrics, and compare results with earlier periods.
Set up cognee and run a first Python example that stores information and retrieves it with a question. Covers virtual environments, API key configuration, optional packages, and basic troubleshooting.
Build a workflow for importing large collections of audio, email, documents, or chats into knowledge pages. Test varied samples first, track progress in a persistent JSON file, and verify outputs before marking work complete.
Manage shared project tasks in Beads, from finding available work and claiming tasks to tracking dependencies, recording follow-up work, and closing completed items. Keep project status available across sessions and handoffs.
Diagnoses storage failures in GKE, Google's managed Kubernetes service, including stuck Pods, disk attachment errors, storage pressure, and missing volume expansion. It provides diagnostic commands and reviewable configuration patches for deployment through GitOps.
Guide an AI agent through ClawWork, an economic survival simulation where task rewards must cover API token costs. Defines a daily choice between work and learning, artifact submission, knowledge storage, and priorities based on the remaining balance.
Audit Claude, Codex, or Pi configuration, instruction conflicts, hooks, and MCP connections to external tools. It also checks safeguards for maintaining AI-assisted projects and returns prioritized findings with evidence and concrete corrective or diagnostic steps.
Keeps multi-step work organized with Markdown files for the plan, research notes, and final deliverable. Tracks completed phases, decisions, and errors so the agent can revisit goals and resume work with durable records.
Coordinate specialist agents in Claude Flow under a lead agent. Distribute development or research tasks, use voting to make decisions, preserve shared knowledge, and pause or resume work through managed sessions.
Use DeepAPI to search the web, collect website and social platform data, and produce sourced research. It also routes tasks to services for public website actions, email, image generation, and persistent agent memory.
Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory
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