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记忆与上下文
筛选文章 记忆与上下文
记忆与上下文
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Should an agent keep going or start a fresh attempt? Use When Agents Slow Down, Reflexion, Hyperband, and agent evaluation to compare continued revision with independent attempts under reproducible budgets.
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Why long tasks need more than one growing conversation How OpenAI Agents API and Anthropic Managed Agents use sessions, context windows, compaction, and persistent state for long-running agents.
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RTK: filter shell output before it reaches a coding agent RTK filters test, Git, search, and build noise before command output enters model context, applying context engineering at the tool-output boundary.
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Free Vision Skill: visual evidence for text agents VEP/1 turns images into short evidence packets. Provider fallback, caching, and credential storage manage cost and reliability for text agents.
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Loop Engineering Harness: controlling agent iterations Break down planning, execution, evaluation, state management, and stopping rules to keep multi-step agent tasks controlled and traceable.