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CRQ-54: Deterministic CRQ Parser #29

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CRQ-54: Document deterministic CRQ parser
Sep 12, 2025
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Docs: Add .emacs.d/ to .gitignore
Sep 13, 2025
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4 changes: 3 additions & 1 deletion .gitignore
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.emacs.d/

36 changes: 36 additions & 0 deletions docs/crq_standardized/CRQ-54-agent-communication-analysis.md
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# CRQ-54: Agent Communication Mirroring and Analysis

## Objective

To establish a robust system for mirroring and analyzing communications between human developers and AI agents (e.g., CodeRabbitAI) within the project's Pull Request workflow. This includes:

1. Mirroring PR descriptions and comments to the local file system, structured by CRQ.
2. Developing tools to analyze these mirrored communications to extract predicates, traits, and patterns of interaction.
3. Facilitating the development of a "proc file system" for agent interactions to enable programmatic analysis and understanding of agent behavior and contributions.

## Scope

* Development of scripts to fetch PR data and comments from GitHub and store them as Markdown files with YAML front matter.
* Implementation of a Rust program (`response_analyzer`) to parse these Markdown files and extract predefined predicates and traits.
* Integration of these tools into the development workflow to automatically capture and analyze agent communications.

## Deliverables

* `mirror_pr_to_fs.sh`: Script to mirror PRs and comments to the file system.
* `ping_coderabbitai.sh`: Script to conditionally ping CodeRabbitAI.
* `process_all_crq_branches.sh`: Orchestration script to process all CRQ branches for mirroring.
* `response_analyzer` Rust crate: Program to analyze mirrored responses and extract predicates.
* Updated documentation on the process and analysis results.

## Dependencies

* GitHub CLI (`gh cli`)
* `jq` (for JSON parsing)
* Rust toolchain
* Existing CRQ branches for data collection.

## Success Criteria

* All relevant PRs and their comments are successfully mirrored to the local file system in the specified `comms/git/<CRQ_ID>/` structure.
* The `response_analyzer` program successfully extracts defined predicates and traits from the mirrored data.
* The analysis provides actionable insights into agent communication patterns and effectiveness.