Unverified50% confidenceFactExact time
The reasoning loop contains three phases—Thought, Action, and Observation—and each iteration requires feeding the complete historical context back into the model, causing token consumption to grow in a stepwise fashion.
1
Sources
50%
Confidence
Long-term
Relevance
9/5/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedUnder the ReAct paradigm, the model goes through a Thought → Action → Observation cycle at each step, with each cycle constituting one complete LLM call.77% similarUnverifiedIn each iteration of the loop, an agent needs to repackage the system prompt, conversation history, tool descriptions, and all outputs from previous steps before feeding them into the model, causing token consumption to grow linearly or even super-linearly with the number of steps.75% similarVerifiedThe ReAct framework forms a three-part cycle of Thought → Action → Observation, which differs from Chain-of-Thought (CoT) that reasons only within the model internally.75% similarVerifiedReAct requires the model to explicitly output a "Thought—Action—Observation" triplet at each step, forming a traceable decision trajectory.74% similarUnverifiedThe workflow loop of this methodology is: Plan → Prompt → Generate → Review → Iterate.73% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/860428API
curl https://kongchang.com/api/v1/knowledge/claims/860428MCP
get_claim(id=860428)