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Research & Knowledge
Agents for research, retrieval, memory, knowledge bases, RAG, GraphRAG, and long-context synthesis.
Which technical function should the agent perform?
Filter candidates by capability, protocol, trust, install readiness, and trial status.
- Collect and synthesize source-backed research.
- Build reusable knowledge assets.
- Preserve citations and assumptions for review.
Recommended trials and bundles
This skill automates the collection and deduplication of trending memes from the web and writes new entries to the Dify knowledge base.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill provides local memory for OpenClaw agents by capturing conversations, extracting facts, and recalling relevant knowledge before each turn.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
MemFree optimizes productivity through hybrid AI search, enhancing data retrieval and workflow automation.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill stores and recalls memories with semantic vector search, enabling cross-session recall and targeted memory retrieval for AI agents.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill automates memory maintenance for OpenClaw agents by reviewing daily notes, suggesting MEMORY.md updates, and auto-cleansing old files for a
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps design multi-layer memory architectures from working to temporal knowledge graphs, enabling persistent agents and robust reasoning.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill provides persistent long-term memory for AI agents, storing, recalling, and reasoning across sessions to improve contextual understanding.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill provides complete Memphis 3.6.0 core integration for OpenClaw agents with auto-detection and memory capture.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill provides a lightweight, zero-dependency memory system with categorized, tag-based retrieval to help agents organize knowledge efficiently.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps AI agents persist memory across sessions using Ebbinghaus decay and strength-weighted retrieval.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Review links
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4677 matching candidates for Research & Knowledge. Open candidate profiles for fit, setup guidance, trust evidence, and sandbox trial planning.
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- 02Role categoryOpen the focused review record
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- 04Profile resourcesEvidence, setup, trust, trial, and history files
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