feat: improve maintainers detection [CM-1033]

[mbani01]

This pull request significantly improves the maintainer file detection and analysis logic for the git integration service. The main enhancements include a more robust and flexible approach to identifying maintainer-related files using both static lists and dynamic content-based search (via ripgrep), as well as improved handling and reporting of candidate files and AI-suggested files. Additionally, the changes introduce better error handling and metadata tracking throughout the maintainer extraction process.

Maintainer file detection and analysis improvements:

• Added dynamic maintainer file discovery using ripgrep to search for maintainer-related keywords across the repository, with fallback to os.walk if ripgrep fails. This enables more accurate and comprehensive detection of potential maintainer files.
• Expanded and refined the static list of possible maintainer file names and valid file extensions, and introduced content validation keywords and exclusion rules to improve candidate file filtering.
• Implemented a new extraction flow that prioritizes previously saved maintainer files, then tries static and dynamic candidates, and finally falls back to AI-based file detection as a last resort. The process now tracks and returns candidate files and AI-suggested files as metadata. [1] [2]

Metadata and reporting enhancements:

• Updated the MaintainerResult model to include candidate_files and ai_suggested_file fields, allowing downstream consumers to see which files were considered and which file was suggested by AI.
• Extended the maintainer processing pipeline to record and report candidate files and AI-suggested files in service execution logs and results. [1] [2] [3]

Dependency and utility updates:

• Added the ripgrep tool to the Docker image to support fast and efficient content-based file search.
• Updated imports and utility usage to support the new shell command execution and error handling required by the ripgrep-based search. [1] [2]

These changes collectively make maintainer detection more reliable, transparent, and extensible, while also improving observability for debugging and future enhancements.

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Note

Medium Risk
Modifies the maintainer detection/analysis flow and introduces repo-wide rg searches plus new fallback paths, which could affect accuracy, performance, and execution behavior across many repos.

Overview
Improves maintainer extraction by prioritizing the previously saved maintainer file, then scanning the repo for likely governance files (expanded static filename list + ripgrep keyword search with filtering/scoring), and only falling back to AI filename selection as a last resort.

Adds observability by returning/storing candidate_files and ai_suggested_file on MaintainerResult and persisting them in ServiceExecution.metrics, and updates the git-integration Docker runner image to include ripgrep.

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[Copilot]

Pull request overview

This PR improves maintainer file detection in the git integration service by adding a multi-step discovery and analysis flow that combines static filename matching, dynamic ripgrep-based content search, and an AI fallback, while also surfacing more metadata about what was tried.

Changes:

• Added ripgrep-based repo scanning (rg --files and keyword search) with fallback to os.walk, plus scoring/filtering of dynamic candidates.
• Refactored maintainer extraction to prioritize a previously saved maintainer file, then analyze top candidates, then use AI file suggestion as a last resort.
• Extended MaintainerResult and service execution metrics to include candidate_files and ai_suggested_file; added ripgrep to the Docker image.

Reviewed changes

Copilot reviewed 3 out of 3 changed files in this pull request and generated 4 comments.

File	Description
services/apps/git_integration/src/crowdgit/services/maintainer/maintainer_service.py	New candidate discovery + fallback extraction flow; logs and metrics now include candidate/AI-suggested file metadata.
services/apps/git_integration/src/crowdgit/models/maintainer_info.py	Adds new result metadata fields (candidate_files, ai_suggested_file).
scripts/services/docker/Dockerfile.git_integration	Installs ripgrep in the runner image to support dynamic search.

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