Add reflected memory and update decompose/orchestrate skills
Adds decisions and process-lessons from recent reflections. Updates decompose and orchestrate SKILL.md with operational improvements. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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# Architecture Decisions
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## Git worktrees for container agent task isolation
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Each container agent gets its own git worktree branch. This prevents file conflicts between parallel agents and makes merging results straightforward with standard git operations.
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## No hardcoded concurrency limit
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The `max_concurrent` value is set by the user during `/decompose`, not baked into the skill. Different tasks have different parallelism needs — a refactor across 10 files can run 10 agents, while a sequential pipeline needs 1-2.
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## Container agents launched with docker run -d (no --rm)
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Using `-d` without `--rm` ensures container logs survive for debugging. The orchestrator checks exit codes and retrieves logs from stopped containers. Cleanup is explicit, not automatic.
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## Harness design is highest-leverage for agent quality
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Research showed LangChain benchmark scores jumped from 52.8% to 66.5% from harness improvements alone (context injection, tool selection, prompt structure). Model choice matters less than giving the model good context and tools.
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## Keep harness layers to 3-5 (95% step problem)
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Each harness layer that must succeed is a multiplicative failure point. At 95% reliability per step, 10 steps = 60% overall success. Keep the critical path short — 3-5 layers max.
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