Unverified50% confidenceSolutionExact time
One of the harness's core tasks is context budget allocation: determining which information stays resident, which is retrieved on demand, and which should be compressed into summaries or symbolized indexes.
1
Sources
50%
Confidence
Long-term
Relevance
10/12/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedKey implementation points for building a knowledge base include document preprocessing and vector storage, retrieval strategy optimization (hybrid retrieval, re-ranking), context management and Token optimization, and privacy protection and data security.66% similarUnverifiedThe biggest bottleneck when scaling context is historical tool outputs, including text chunks from past retrievals, tool call and result pairs, and file search records.65% similarUnverifiedBuilding a knowledge base with RAG involves three steps: data collection, text chunking, and vectorized storage.64% similarUnverifiedBy attaching metadata tags such as team, feature, user, or environment to requests, the total bill can be broken down by dimension to identify cost sources.64% similarUnverifiedElasticsearch in production typically requires configuring dedicated Master nodes, Data nodes, and Ingest nodes, along with manually planning shard counts—too many shards slow down queries, while too few limit write throughput.64% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1012332API
curl https://kongchang.com/api/v1/knowledge/claims/1012332MCP
get_claim(id=1012332)