agentleFS
YangsonHungYangsonHung/awesome-agent-skills/skills/en/git-weekly-report/SKILL.md

git-weekly-report

Skill18 starsChanged 5 days agoMITView on GitHub

Use when summarizing git commit history into a structured daily or weekly work report.

1 other project uses a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

8 rules. About 0 are common, 6 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈6

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use this skill when the user asks for:

    line 14
  2. Distinctive:

    Do not use this skill for:

    line 24
  3. Very specific:

    Daily report: if user says "yesterday", "today", or "daily report", default --since to yesterday and --until to today.

    line 33
  4. Very specific:

    Weekly report: if user says "this week" or "weekly report", default --since to last Monday and --until to today.

    line 34
  5. Distinctive:

    Read the JSON output. The script provides structured commit data grouped by repository.

    line 44
  6. Distinctive:

    Use weekly-report-format.md as the categorization guide to classify commits by type.

    line 45
  7. Distinctive:

    Use weekly-report-template.md as the output structure when generating the final report.

    line 46
  8. Distinctive:

    When commits exceed 50 per repository, summarize by category rather than listing every commit individually.

    line 85

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Git Weekly Report

Overview

Extract git commit logs and generate a structured daily or weekly report. The output groups recent work into completed items, in-progress work, highlights, plans, and risks so commit history can be reused for standups, daily reports, weekly reports, or project summaries.

When to Use

Use this skill when the user asks for:

  • Generating a weekly report or daily report from git commits
  • Summarizing yesterday's or today's git activity
  • Summarizing recent git activity across one or more repositories
  • Reviewing what work was done over a date range
  • Compiling commit history into a categorized report
  • Preparing a daily standup summary from commits

Do not use

Do not use this skill for:

  • Code review of specific changes (use code-reviewer instead)
  • Inspecting a single commit in detail
  • Git operations other than log extraction (branching, merging, etc.)
  • Non-git-related report generation

Instructions

  1. Determine the date range and report type:
    • Daily report: if user says "yesterday", "today", or "daily report", default --since to yesterday and --until to today.
    • Weekly report: if user says "this week" or "weekly report", default --since to last Monday and --until to today.
    • Otherwise: default to last 7 days. Accept user overrides.
  2. Determine the author filter if the user specifies one. Default: all authors.
  3. Determine repository path(s). Default: current working directory. If the user mentions multiple projects, collect all paths.
  4. Run the script:
python3 scripts/git_weekly_report.py --since <YYYY-MM-DD> --until <YYYY-MM-DD> [--author <name>] [--repo <path1> <path2> ...]
  1. Read the JSON output. The script provides structured commit data grouped by repository.
  2. Use weekly-report-format.md as the categorization guide to classify commits by type.
  3. Use weekly-report-template.md as the output structure when generating the final report.
  4. For "next-week plans" and "risks" sections: ask the user if they have items to add, since these are not derivable from git logs. For daily reports, omit these sections unless the user requests them.
  5. Present the final Markdown report. Save to a file if the user requests it.

Script Usage

# Default: last 7 days, current directory
python3 scripts/git_weekly_report.py

# Specific date range
python3 scripts/git_weekly_report.py --since 2026-04-21 --until 2026-04-28

# With author filter
python3 scripts/git_weekly_report.py --since 2026-04-21 --author "Yang"

# Multiple repositories
python3 scripts/git_weekly_report.py --since 2026-04-21 --repo /path/to/project-a /path/to/project-b

# Save output to file
python3 scripts/git_weekly_report.py --since 2026-04-21 --output /tmp/weekly.json

# Include merge commits
python3 scripts/git_weekly_report.py --since 2026-04-21 --merges

JSON Output Structure

The script outputs JSON with this structure:

  • date_range: { since, until } — the queried date range
  • author_filter: string or null — applied author filter
  • repositories: array of { path, name, commit_count, commits }
  • total_commits: total across all repositories

Each commit has: hash, short_hash, author, date, subject, body, refs.

Report Generation

When commits exceed 50 per repository, summarize by category rather than listing every commit individually. Always preserve short hashes for traceability.

For the "In Progress" section, look for signals like: WIP, TODO, partial implementations, or incomplete feature branches.

For the "Highlights" section, identify: breaking changes, security fixes, major features, or commits touching critical paths.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.