| name | cv-data-management |
| description | CV Building Mode. Guidelines for adding new professional experience, projects, or skills to the cv-data repository. |
CRITICAL INSTRUCTION: There are model and runtime-specific variances for agents running in this environment. If you are a Gemini Agent in Gemini CLI, you will use Gemini_Tasks. If you are an OpenAI Agent running under Codex, you will use Codex_Tasks.
CV Data Management (CV Building Mode)
This workflow ensures new artifacts in the cv-data/ directory are high-quality, fact-based, and indexable.
File Standards
- Format: Markdown (
.md).
- Voice: 3rd Person, Objective/Journalistic (e.g., "The Candidate architected...").
- Location: Place new files in the appropriate subdirectory of
cv-data/.
Media Mentions & Articles
- Body Content: MUST contain the FULL TEXT of the article. Do not summarize the content in the body.
- Summary: The summary must be placed strictly in the JSON FrontMatter
summary field.
Mandatory JSON FrontMatter
Every file must start with a JSON FrontMatter block for indexing:
---
{
"title": "Project Review: <Project Name>",
"summary": "A concise (2-3 sentence) overview.",
"keywords": ["Skill 1", "Skill 2"],
"date": "YYYY-MM-DD",
"document_type": "Project Review",
"domain": "Software Engineering"
}
---
Validation
Run the linter after any modification:
python3 AGENT_Tasks/Maintenance/lint_cv_data.py
