Loading...
Loading...
Found 8 Skills
Use when compressing agent context, implementing conversation summarization, reducing token usage in long sessions, or asking about "context compression", "conversation history", "token optimization", "context limits", "summarization strategies"
This skill should be used when the user asks to "compress context", "summarize conversation history", "implement compaction", "reduce token usage", or mentions context compression, structured summarization, tokens-per-task optimization, or long-running agent sessions exceeding context limits. A core context engineering skill — also activates when the user mentions "context engineering" or "context-engineering" in the context of managing token budgets and session longevity.
Use when conversation context is too long, hitting token limits, or responses are degrading. Compresses history while preserving critical information using anchored summarization and probe-based validation.
Design and evaluate compression strategies for long-running sessions
Search-aware context compression workflow for agent-studio. Use pnpm hybrid search + token-saver compression, then persist distilled learnings via MemoryRecord.
Context compression and summarization methodology. Techniques for reducing token usage while preserving decision-critical information.
[Tooling & Meta] Compress conversation context to optimize tokens
Compress long conversation histories, large code files, research results, and documents by 70% without losing critical information. Triggers when context window fills up, when summarizing previous steps in multi-step tasks, before loading large files into context, or on "summarize", "compress", "reduce context", "save tokens".