aming-claw-hn-demo-during-work
CommunityMake AI subagents observable in real-time.
Software Engineering#subagents#evidence-collection#ai-observability#aming-claw#timeline-dag#observer-lanes
Authoramingclawdev
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill addresses the challenge of invisible AI subagents during implementation and provides structured guidance to collect and show evidence through a timeline DAG, observer lanes, and gate mechanisms.
Core Features & Use Cases
- Timeline DAG capture: orchestrates event sequencing from dispatch to handoff.
- Observer/subagent lanes: clarifies decision origins and artifact provenance.
- Dispatch gates and evidence inspector: enforces safe, auditable handoffs.
- Isolated worktrees and append-only evidence: preserves history for replay and verification.
- Governance-ready demonstrations: supports requirement anchors and safe startup.
Quick Start
Open the HN demo workspace and start collecting timeline DAG evidence across observer and subagent lanes.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: aming-claw-hn-demo-during-work Download link: https://github.com/amingclawdev/aming-claw/archive/main.zip#aming-claw-hn-demo-during-work Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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