Canon Boundary Guard is a source-bundle frame for ChatGPT Projects. It gives ChatGPT a structured protocol for keeping inspected evidence separate from chat material, agent-control instructions, model assumptions, and generated drafts — so nothing silently becomes accepted truth.Documentation Index
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Introduction
Understand the problem Canon Boundary Guard solves and when to use it.
Quickstart
Set up the bundle in a ChatGPT Project in under five minutes.
Source Classes
Learn the five provenance layers — L0 through L3 and L1A.
Protocol Reference
Full rules for classifying sources, running the gate, and producing dossiers.
How it works
Canon Boundary Guard works by combining a Project Instructions anchor with a zipped source bundle uploaded to your ChatGPT Project. When a new session starts, ChatGPT locates the bundle, runs a mandatory Status Check, and activates the provenance-control frame before any substantive output.Create and upload the bundle
Zip the
canon-boundary-guard-gpt/ folder and add it to your ChatGPT Project files.Paste the Project Instructions
Copy
PROJECT_CUSTOM_INSTRUCTIONS.txt into the Project instructions field.Start a new chat
Open a new chat inside the Project. ChatGPT will run the Status Check bootstrap automatically.
Key concepts
Operating Modes
Mode A, B, and C control how much scrutiny is applied before persistent output.
Persistence Boundary
Understand exactly what counts as a persistent write and when the gate runs.
State and Recovery
Manage SESSION_STATE and recover from lost context safely.
Scratch and Canon Zones
Learn the /mnt/data layout and the rules for promoting scratch work.
Canon Boundary Guard reduces silent promotion — it is not a hard enforcement mechanism. ChatGPT can still skip instructions or lose context. The frame is a working discipline, not a guarantee.