Unverified50% confidenceFactExact time
DarKnight is a self-improving agent framework designed to run a locally hosted open-weight VLM on a single workstation GPU within investigators' own Tor crawling environment, without relying on third-party services and without requiring separate training for each market.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/15/2026
First Seen
Valid until: 1/13/2027
Sources
Related Entities
Related Claims
UnverifiedOneCLI 将自身定位为面向团队的开源沙箱化 Agent harness（智能体运行框架）59% similarUnverifiedv0.9 allows defining an agent as a callable function that receives the runtime at the start of each run and returns a define_deep_agent definition, dynamically selecting the model, instructions, skills, MCP servers, and sandbox.59% similarVerifiedAgentic RAG grants the model autonomous planning capability, enabling it to assess whether information is sufficient, decide whether to perform multi-round retrieval, choose which tools or data sources to invoke, and carry out self-reflection and iterative correction.58% similarUnverifiedBuilding an Agent that can call tools requires selecting a model with a hammer icon (indicating tool-calling support), such as OpenAI, Moonshot AI, and DeepSeek.58% similarUnverifiedFrontierCode places greater emphasis on a model's ability to function as an autonomous Agent compared to benchmarks like HumanEval and SWE-bench57% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1038917API
curl https://kongchang.com/api/v1/knowledge/claims/1038917MCP
get_claim(id=1038917)