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git2linkedin

Generate feature-based and confidentiality-safe English LinkedIn Experience drafts directly from commit messages. Use when asked to write LinkedIn experience text from real commit activity for all-time or a specific date range (`since`/`until` in YYYY-MM-DD), while avoiding repository statistics and internal/confidential implementation details.

personAuthor: jakexiaohubgithub
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Git2LinkedIn

Overview

Generate a LinkedIn Experience draft from git history by directly reading commit messages and converting them into feature-focused, business-relevant, and confidentiality-safe bullets.

Workflow

  1. Collect required inputs:
  • role (required)
  • company (required)
  1. Collect optional inputs:
  • repo (default .)
  • since (YYYY-MM-DD)
  • until (YYYY-MM-DD)
  • author (default: current git user)
  • out (optional markdown output path)
  • max-commits (default 400)
  1. Run the extractor:
# All-time
python3 skills/git2linkedin/scripts/git_history_extract.py \
  --role "Senior Software Engineer" \
  --company "Acme"

# Date range
python3 skills/git2linkedin/scripts/git_history_extract.py \
  --role "Senior Software Engineer" \
  --company "Acme" \
  --since 2025-01-01 \
  --until 2025-12-31
  1. Convert JSON output into final LinkedIn text:
  • Write one short English summary sentence.
  • Write 4-6 impact bullets.
  • Focus on end-user value and business relevance.
  • Avoid repository metrics, commit hashes, file paths, and internal identifiers.
  1. Handle empty ranges explicitly:
  • If commit list is empty, explain that no commits were found and suggest widening the date range or changing author.

Output Contract

Use these JSON fields:

  • summary: baseline sentence for LinkedIn experience
  • feature_highlights: feature-oriented bullet candidates
  • end_user_outcomes: user-facing outcomes
  • business_relevance: why this work matters for role/business goals
  • source_mode: extraction mode metadata (direct-commit-messages)
  • guidance: fallback suggestion when history is empty

Guardrails

  • Keep output in English unless user asks otherwise.
  • Keep bullets concise and outcome-focused.
  • Keep sentence style mostly passive and neutral; avoid first-person phrasing (I improved, I enhanced, etc.).
  • Do not include repository statistics.
  • Do not expose commit hashes, file paths, issue IDs, URLs, or raw commit messages.
  • Do not invent confidential product details; keep language high-level and safe for public profiles.