bicameral-ingest

Ingest implementation-relevant decisions from source documents into the decision ledger.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/BicameralAI/bicameral-mcp --skill bicameral-ingest
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bicameral-ingest
Source: https://github.com/BicameralAI/bicameral-mcp/tree/main/.claude/skills/bicameral-ingest
Command: npx skills add https://github.com/BicameralAI/bicameral-mcp --skill bicameral-ingest

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Ingest implementation-relevant decisions from source documents into the decision ledger to ensure traceability between product decisions and code.

Core Features & Use Cases

  • Boundary detection and pre-ingest segmentation for transcripts, PRDs, Slack threads, and design documents.
  • Grounding support for both code-region based ingests and natural-language ingests, with optional post-ingest context-sentry reconciliation.
  • End-to-end workflow orchestration (preflight, ingest, and gap-judgment) to surface business-tied decisions and drift.

Quick Start

Feed source documents to bicameral-ingest to seed the decision ledger.

Frequently Asked Questions about bicameral-ingest

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

FAQPage Schema
How do I ingest decisions from source documents into a traceable ledger?▼

To ingest decisions into a traceable ledger, feed source documents like PRDs or Slack threads to the Skill. It handles boundary detection, pre-ingest segmentation, and grounding to capture business-tied decisions for future pinning and review.

What is decision traceability and how does boundary detection work for transcripts?▼

Decision traceability links product decisions to code regions. Boundary detection works by performing pre-ingest segmentation on transcripts and design documents to isolate implementation-relevant decisions before capturing them in the ledger.

Can I use natural language formats for grounding decisions without strict code regions?▼

Yes, you can use natural language formats for grounding decisions without code regions. The ingestion process supports both code-region based ingests and natural-language ingests to ensure business-tied decisions are captured for review.

How do I surface drift and ensure only business-tied decisions are captured during ingestion?▼

To surface drift and ensure only business-tied decisions are captured, use the end-to-end workflow orchestration. It runs preflight, ingest, and gap-judgment phases with optional gates to filter out non-compliant entries.

What is the best way to manage compliance and traceability for product decisions across Slack threads?▼

The best way to manage compliance and traceability for product decisions across Slack threads is to ingest them into a decision ledger. Boundary detection and pre-ingest segmentation isolate the relevant decisions for compliance tracking.