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Compress conversation history when context fills up. Use anchored iterative summarization to preserve file changes, decisions, and session intent without losing critical details.
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Orchestrates all 210 specialist agents simultaneously. Auto-discovers skills, MCP servers, repos. Used for comprehensive/360/full-analysis tasks.
Apify Actor Development
Actorization converts existing software into reusable serverless applications compatible with the Apify platform. Actors are programs packaged as Dock
Generate output schemas (dataset_schema.json, output_schema.json, key_value_store_schema.json) for an Apify Actor by analyzing its source code. Use wh
Universal Web Scraper
Auto-captures corrections and confirmations from every conversation → writes to ~/.claude/session-queue.jsonl → processed by Stop hook into memory files.
| name | context-compression |
| description | Compress conversation history when context fills up. Use anchored iterative summarization to preserve file changes, decisions, and session intent without losing critical details. |
| risk | safe |
| source | community |
When context window is filling up, compress history:
Method (anchored iterative summarization):
Key rule: Structure forces preservation. Use explicit sections as checklists.
Trigger when: conversation > 50k tokens, or /compact requested, or context warning appears.
Full docs: ~/.claude/skills-docs/context-compression-FULL.md
