feat(integrations): add Jira backlog workflows and Jira/GitLab skills

[peteroden]

feat(integrations): add Jira backlog workflows and Jira/GitLab skills

Description

This PR added Jira backlog discovery, triage, execution, and PRD planning workflows, introduced local Jira and GitLab Python skills, and wired those artifacts into collection and plugin packaging so they are available through both dedicated integration bundles and the aggregate HVE Core bundle.

Jira backlog workflows

• Added the new Jira backlog manager and Jira PRD-to-WIT agents to separate orchestration from planning-only PRD issue mapping.
• Added Jira discovery, planning, triage, update, and PRD planning instructions that standardize .copilot-tracking/jira-issues/... artifacts, bounded Jira operations, and review gates.
• Added Jira prompts for discovery, triage, execution, and PRD-driven planning, and updated existing project-planning agents to treat Jira and GitLab as supported integration targets.
• Aligned the Jira backlog update instructions to reference handoff.md consistently during resume and finalize steps.

Jira and GitLab skills

• Added Python 3.11 Jira and GitLab CLIs with environment-variable-based authentication, field-filtered read output, and command surfaces for issue workflows, merge requests, pipelines, jobs, and logs.
• Added matching SKILL.md guides and pyproject.toml stubs, and updated the installer skill docs with local setup guidance for both integrations.

Collections and plugin packaging

• Added dedicated jira and gitlab collection manifests and updated hve-core-all to include the new agents, prompts, instructions, and skills.
• Updated the prompt and instruction indexes plus marketplace metadata so the new capabilities are discoverable.
• Regenerated plugin outputs for plugins/jira, plugins/gitlab, and plugins/hve-core-all.

Related Issue(s)

None

Type of Change

Select all that apply:

Code & Documentation:

• Bug fix (non-breaking change fixing an issue)
• New feature (non-breaking change adding functionality)
• Breaking change (fix or feature causing existing functionality to change)
• Documentation update

Infrastructure & Configuration:

• GitHub Actions workflow
• Linting configuration (markdown, PowerShell, etc.)
• Security configuration
• DevContainer configuration
• Dependency update

AI Artifacts:

• Reviewed contribution with prompt-builder agent and addressed all feedback
• Copilot instructions (.github/instructions/*.instructions.md)
• Copilot prompt (.github/prompts/*.prompt.md)
• Copilot agent (.github/agents/*.agent.md)
• Copilot skill (.github/skills/*/SKILL.md)

Note for AI Artifact Contributors:

• Agents: Research, indexing/referencing other project (using standard VS Code GitHub Copilot/MCP tools), planning, and general implementation agents likely already exist. Review .github/agents/ before creating new ones.
• Skills: Must include both bash and PowerShell scripts. See Skills.
• Model Versions: Only contributions targeting the latest Anthropic and OpenAI models will be accepted. Older model versions (e.g., GPT-3.5, Claude 3) will be rejected.
• See Agents Not Accepted and Model Version Requirements.

Other:

• Script/automation (.ps1, .sh, .py)
• Other (please describe):

Sample Prompts (for AI Artifact Contributions)

User Request:

Discover existing Jira issues for this PRD, prepare a reviewed handoff for the backlog updates, and show the latest GitLab pipeline jobs for the related project.

Execution Flow:

• The Jira prompts route to the new Jira backlog manager or Jira PRD-to-WIT agent and create planning artifacts under .copilot-tracking/jira-issues/<workflow>/<scope>/.
• The Jira instruction set drives discovery, triage, planning, and execution flows while keeping Jira mutations behind explicit review and autonomy gates.
• The Jira skill runs fields, search, get, comments, create, update, transition, and comment against the configured Jira instance.
• The GitLab skill runs merge request, pipeline, job, and job-log commands against the configured GitLab project.
• The updated collections and generated plugins surface those agents, prompts, instructions, and skills through the jira, gitlab, and hve-core-all packages.

Output Artifacts:

• .copilot-tracking/jira-issues/discovery/<scope>/planning-log.md, issue-analysis.md, and handoff.md
• .copilot-tracking/jira-issues/triage/<date>/triage-plan.md and planning-log.md
• .copilot-tracking/jira-issues/prds/<artifact>/artifact-analysis.md, issues-plan.md, and handoff.md
• JSON or field-filtered terminal output from .github/skills/jira/jira/scripts/jira.py and .github/skills/gitlab/gitlab/scripts/gitlab.py
• Generated packaging metadata and catalog docs in plugins/jira, plugins/gitlab, and plugins/hve-core-all

Success Indicators:

• Jira and GitLab entries appear in .github/prompts/README.md, .github/instructions/README.md, .github/plugin/marketplace.json, and the generated plugin READMEs.
• The required automation checks pass, and the collection metadata validates after regeneration.
• The Jira workflows create the expected .copilot-tracking/jira-issues/... planning artifacts and can resume from handoff-logs.md when execution is restarted.

For detailed contribution requirements, see:

• Common Standards: docs/contributing/ai-artifacts-common.md - Shared standards for XML blocks, markdown quality, RFC 2119, validation, and testing
• Agents: docs/contributing/custom-agents.md - Agent configurations with tools and behavior patterns
• Prompts: docs/contributing/prompts.md - Workflow-specific guidance with template variables
• Instructions: docs/contributing/instructions.md - Technology-specific standards with glob patterns
• Skills: docs/contributing/skills.md - Task execution utilities with cross-platform scripts

Testing

• Passed npm run lint:md
• Passed npm run spell-check
• Passed npm run lint:frontmatter
• Passed npm run validate:skills
• Passed npm run lint:md-links
• Passed npm run lint:ps
• Passed npm run plugin:generate
• Passed npm run plugin:validate with one existing non-blocking warning about skill|.github/skills/experimental/vscode-playwright not appearing in a themed collection
• Security review found no sensitive or NDA content, no missing referenced files, no non-inclusive language concerns, and no external runtime dependencies added in the new Jira and GitLab pyproject.toml files
• Diff-based review confirmed the new Jira and GitLab assets are wired into collection manifests, marketplace metadata, prompt indexes, and generated plugin packages
• Manual testing was performed

Checklist

Required Checks

• Documentation is updated (if applicable)
• Files follow existing naming conventions
• Changes are backwards compatible (if applicable)
• Tests added for new functionality (if applicable) (N/A — no test files were added in this diff)

AI Artifact Contributions

• Used /prompt-analyze to review contribution
• Addressed all feedback from prompt-builder review
• Verified contribution follows common standards and type-specific requirements

Required Automated Checks

The following validation commands must pass before merging:

• Markdown linting: npm run lint:md
• Spell checking: npm run spell-check
• Frontmatter validation: npm run lint:frontmatter
• Skill structure validation: npm run validate:skills
• Link validation: npm run lint:md-links
• PowerShell analysis: npm run lint:ps
• Plugin freshness: npm run plugin:generate

Security Considerations

• This PR does not contain any sensitive or NDA information
• Any new dependencies have been reviewed for security issues (N/A — the new Jira and GitLab pyproject.toml files do not add external runtime dependencies)
• Security-related scripts follow the principle of least privilege (N/A — no security scripts changed in this diff)

Additional Notes

• npm run plugin:validate completed with an existing non-blocking warning about skill|.github/skills/experimental/vscode-playwright not appearing in a themed collection.
• If Jira prompt validation in the editor reports unknown Jira agents, validate against the aggregate bundle by running pwsh ./scripts/extension/Prepare-Extension.ps1 -Collection collections/hve-core-all.collection.yml. The Jira workflow artifacts are included in jira and hve-core-all, but not in the narrower default hve-core bundle.

[WilliamBerryiii]

@peteroden - I've got most of the Python UV and PyTest system in place ... but don't yet have the blockers in for codecov. Can you try to see if you can get your skill library's python code some unit tests (up to >80% code coverage)?

You can follow the format here: https://github.com/microsoft/hve-core/tree/main/.github/skills/experimental/powerpoint until I've got better contributing guidelines in-place for skill layout and folder structure (and the automation to validate).

Give it an "old college try" and get as far as you can. I'm chill with taking in a "best effort" on skills, until I have the automation to enforce rigor.

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 86.01%. Comparing base (2c2f92f) to head (4a08d92).

Additional details and impacted files

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  Misses        737      737           

Flag	Coverage Δ
pester	86.01% <ø> (ø)

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[peteroden]

@WilliamBerryiii, test added with pretty solid coverage and uv.lock added in alignment with the powerpoint skill structure. I also added pyright for static type checking. Might be a nice add for the powerpoint skill in the future as well.