Auto-summarization

Wrap any ChatMemory so it compacts oldest messages into a summary whenever stored tokens exceed a budget.

compileBudget trims per-request. createAutoSummarizingMemory trims at rest: once a session grows past maxTokens, the oldest (non-summary) messages get folded into a single summary message via your summarizer, then persisted. Idempotent — summaries are tagged and never re-summarized.

#Install

Ships in @agentskit/core under the subpath:

import { createAutoSummarizingMemory } from '@agentskit/core/auto-summarize'

#Wire it up

import { createAutoSummarizingMemory } from '@agentskit/core/auto-summarize'
import { createInMemoryMemory } from '@agentskit/core'
import { createRuntime } from '@agentskit/runtime'
import { anthropic } from '@agentskit/adapters'

const summarizerAdapter = anthropic({ apiKey: process.env.ANTHROPIC_API_KEY!, model: 'claude-haiku-4-5' })

const memory = createAutoSummarizingMemory(createInMemoryMemory(), {
  maxTokens: 8_000,
  keepRecent: 6,
  summarizer: async messages => {
    const src = messages.map(m => `${m.role}: ${m.content}`).join('\n')
    const result = await runOnce(summarizerAdapter, `Summarize the following chat transcript in 3 bullet points:\n\n${src}`)
    return {
      id: crypto.randomUUID(),
      role: 'system',
      content: result,
      status: 'complete',
      createdAt: new Date(),
    }
  },
  onCompact: info => {
    console.log(`compacted ${info.droppedCount} msgs: ${info.beforeTokens} → ${info.afterTokens} tokens`)
  },
})

const runtime = createRuntime({ adapter: mainAdapter, memory })

#Options

Option	Default	Purpose
`maxTokens`	(required)	Budget trigger
`keepRecent`	`4`	Messages always kept verbatim at the tail
`counter`	`approximateCounter`	Swap for tiktoken for real counts
`summarizer`	(required)	`(messages) => Message` — your compaction prompt
`onCompact`	—	Observability hook

#Summary message shape

Every summary emitted by summarizer gets metadata.agentskitSummary = true attached automatically. That tag is what prevents re-summarization — subsequent compactions leave existing summaries alone.

#See also

Token budget compiler — per-request trimming
Virtualized memory — cap count, not tokens
Hierarchical memory — tiered long-term storage

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