Enforce the Subagent Envelope Contract for standardized execution reporting across subagents.
npx skills add https://github.com/lorehq/lore --skill lore-delegate
Please help me install this Agent Skill. Skill: lore-delegate Source: https://github.com/lorehq/lore/tree/main/.lore/harness/skills/lore-delegate Command: npx skills add https://github.com/lorehq/lore --skill lore-delegate
Delegation across multiple subagents often leads to fragmented context, missed insights, and inconsistent results. The Subagent Envelope Contract provides a disciplined reporting surface so every subagent returns both results and a structured envelope of critical context.
Instruct your AI to apply the envelope contract for every delegation and return an envelope with a report.
High-intent search queries and answers about installing and using this skill.
Multi-agent delegation maintains context by enforcing an envelope contract that requires subagents to return structured execution reports alongside results. This preserves critical context, detects pitfalls, and surfaces topology changes for operator review.
A subagent envelope contract is a standardized reporting surface that ensures every worker returns both execution results and a structured [ENVELOPE-REPORT]. This mechanism guarantees reliable intelligence flow and persistent context across delegated tasks.
Post-return intelligence extraction is handled by a pipeline that processes the returned envelope reports to update Redis hot memory and the Global KB. This workflow captures missed insights and standardizes knowledge management across agents.
Yes, you can standardize subagent execution reporting by applying a worker prompt template that specifies a clear MISSION-DIRECTIVE. This enforces the envelope contract and guarantees a structured report is included with the results.
Context fragments during subagent orchestration because independent workers lack a disciplined reporting surface. Without an enforced envelope contract, execution results return without structured context, leading to missed insights and inconsistent intelligence flow.
Multi-agent delegation relies on a post-return extraction pipeline to update Redis hot memory and the Global KB. Without these memory updates, the system loses persistent context and the ability to reliably surface topology changes.
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