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scbe-claude-crosstalk-workflow

Emit JSON cross-talk packets with session IDs for auditable AI lane handoffs.

6|1|Updated Jan 17, 2026
Search Tags:#audit#codex#claude#json#handoff#packet#cross-talk
One-click install
npx skills add https://github.com/issdandavis/SCBE-AETHERMOORE --skill scbe-claude-crosstalk-workflow
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scbe-claude-crosstalk-workflow
Source: https://github.com/issdandavis/SCBE-AETHERMOORE/tree/main/external/codex-skills-live/scbe-claude-crosstalk-workflow
Command: npx skills add https://github.com/issdandavis/SCBE-AETHERMOORE --skill scbe-claude-crosstalk-workflow

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Enables auditable, deterministic handoffs between parallel AI lanes by emitting structured cross-talk packets with session IDs, lane context, and repairable delivery checks.

Core Features & Use Cases

  • Deterministic cross-lane handoffs: emits and tracks packets with session-scoped identifiers for traceability across artifacts, lane bus, and inbox.
  • Auditability and repair: provides scripts to verify and repair delivery parity between day-specific packets, the GitHub lanes JSONL, and the human inbox mirror.
  • Observability and governance: maintains an auditable trail that supports recovery and review of cross-lane communications.

Quick Start

Use scbe-claude-crosstalk-workflow to start a cross-lane session, emit the initial cross-talk packet, and then run the audit script to verify delivery mirrors.

Frequently Asked Questions about scbe-claude-crosstalk-workflow

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I coordinate auditable handoffs between parallel Claude and Codex workflows?▼

Cross-talk packets are structured JSON payloads containing session-scoped identifiers and lane context, emitted to coordinate initial handoffs, updates, and verification across parallel AI workflows.

How do I verify delivery parity between AI lane JSONL entries and packet artifacts?▼

You verify delivery parity by running the provided audit scripts, which check and repair alignment between day-specific JSON packets, the GitHub lanes JSONL entries, and the human inbox mirror.

Can I use this workflow to recover lost communications between parallel AI lanes?▼

Yes, the workflow maintains an auditable trail with repairable delivery checks that support recovery and review of cross-lane communications across parallel AI lanes.

Does the cross-talk workflow require dependencies to manage AI session context?▼

No dependencies are required to manage AI session context, as the workflow operates independently using JSON packets, JSONL lane entries, and inbox lines to maintain cross-lane coordination.

What is the best way to start a cross-lane session for parallel AI workflows?▼

The best way to start is to initialize the session, emit the initial cross-talk packet with a session ID, and then run the audit script to verify that the delivery mirrors are correctly aligned.

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