Unverified50% confidenceFactExact time
In addition to prompts, context also includes system instructions, retrieved external knowledge, conversation history, tool return results, example samples, and various other components.
1
Sources
50%
Confidence
Long-term
Relevance
10/10/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedThe session log is Harness's "source of truth," and system prompts, model outputs, tool calls and results, sub-agent scheduling, and context injection can all be replayed along the event stream75% similarUnverifiedTaking LLMs as an example, context includes the system prompt, user query, externally retrieved information, historical interaction records, and additional system outputs.74% similarUnverifiedIt is recommended to start simple and evolve gradually: first save conversation history, record task time and status, and manually annotate success and failure cases, then gradually introduce automated analysis tools.71% similarUnverifiedContext engineering focuses on all background information that a model relies on when generating answers, including retrieved documents, conversation history, system settings, and external data, requiring systematic organization and management of information accessible to the model.70% similarUnverifiedThe actual number of tokens consumed by a single user request includes the entire input context (including conversation history, system prompts, tool definitions, etc.) as well as the response content generated by the model.70% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/993256API
curl https://kongchang.com/api/v1/knowledge/claims/993256MCP
get_claim(id=993256)