gh-summary

gh-summary is a skill for Claude Code, Codex from wrannaman/agentic-engineering. It costs 39 tokens per session (1,227 once invoked), scanned A, original, MIT.

A GitHub reporting tool that summarizes your merged pull requests (code changes reviewed and accepted into a project) across one or more repositories and time periods.

In plain words
What is it for?
Use it to review recent work, prepare standup updates, or explain the engineering and business value of your merged pull requests.
Why use it?
It turns a list of code changes into a clear account of what you completed and why it mattered, making standups and contribution reviews easier.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/wrannaman/agentic-engineering/gh-summary
Any agent
npx skills add wrannaman/agentic-engineering --skill gh-summary
Clone the repo
git clone --depth 1 https://github.com/wrannaman/agentic-engineering

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for gh-summary

README.md
[![agentmods](https://agentmods.dev/badge/skills/wrannaman/agentic-engineering/gh-summary.svg)](https://agentmods.dev/skills/wrannaman/agentic-engineering/gh-summary)
Your own site
<a href="https://agentmods.dev/skills/wrannaman/agentic-engineering/gh-summary"><img src="https://agentmods.dev/badge/skills/wrannaman/agentic-engineering/gh-summary.svg" alt="Measured on agentmods" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,227 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00039 $0.01227
Opus 5 $0.00019 $0.00613
Sonnet 5 $0.00008 $0.00245
Haiku 4.5 $0.00004 $0.00123

Measured 4d ago against content hash 9b220cda4c34, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

gh-summary scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/analysis/gh-summary/SKILL.md · 141 lines

How it starts

The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GitHub Contribution Summary

Summarize merged PRs and interpret the business/engineering value delivered.

Usage

  • /gh-summary - Current repo, last 30 days
  • /gh-summary last 7 days - Current repo, last 7 days
  • /gh-summary since January 1st - Current repo, since date
  • /gh-summary owner/repo1 owner/repo2 last 30 days - Multiple repos

Arguments

Arguments can be provided in any order. The skill will parse:

  1. Repos (optional): Comma or space-separated list of repos in owner/repo format

    • If omitted, uses the current working directory's repo
    • Examples: owner/repo-name, owner/repo1,owner/repo2
  2. Time range (optional): Natural language time specification

    • Relative: "last 7 days", "last 2 weeks", "last 30 days"
    • Absolute: "since January 1st", "since 2026-01-01"
    • If omitted, defaults to "last 30 days"

Process

Step 1: Parse Arguments

Parse the ARGUMENTS string to extract:

  • repos: List of repos, or empty (meaning current repo)
  • time_range: Natural language time, or "last 30 days" default

Convert time range to ISO date format (YYYY-MM-DD) for the gh search query.

Step 2: Get GitHub Username

gh api user --jq '.login'

Step 3: Fetch PRs for Each Repo

For each repo (or current repo if none specified):

gh pr list --repo {repo} --author {username} --state merged \
  --search "merged:>={iso_date}" --limit 200 \
  --json number,title,body,mergedAt,additions,deletions,changedFiles,commits,url

If no --repo flag needed (current repo), omit it:

gh pr list --author {username} --state merged \
  --search "merged:>={iso_date}" --limit 200 \
  --json number,title,body,mergedAt,additions,deletions,changedFiles,commits,url

Step 4: Calculate Stats

From the PR data, calculate:

  • PR count: Total number of PRs merged
  • Lines added: Sum of additions across all PRs
  • Lines removed: Sum of deletions across all PRs
  • Net lines: additions - deletions
  • Files changed: Sum of changedFiles across all PRs
  • Commits: Sum of commit counts (length of commits array) across all PRs
  • Repos touched: Count of unique repos (if multi-repo)

Read the full file on GitHub · 141 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 141 lines · 39 tokens per session scan A 9b220cda4c34

Subscribe to this mod's changes

gh-summary is a skill published in the GitHub repository wrannaman/agentic-engineering (2 stars, last pushed 4mo ago), licensed MIT. It adds 39 tokens to every session and 1,227 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens

chat-perf

Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.

microsoft/vscode · 51 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens