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Official agent skill

Statistics Infographic

by github in github/gh-aw

Generate a readable six-panel repository statistics infographic from validated JSON, with exact arithmetic and independent raw GitHub/Git reconciliation.

OfficialMITAuto-check passedMedia & Creative

Install Statistics Infographic

skills CLI
$ npx skills add github/gh-aw --skill statistics-infographic -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install github/gh-aw statistics-infographic --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/github/gh-aw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/skills/statistics-infographic .claude/skills/statistics-infographic && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
statistics-infographic
GitHub stars
5.4k
Token cost
~1.3k tokens
SKILL.md length
506 words
Files
9 (incl. scripts, references)
Skills in repo
53
Repo updated
First seen
Licence
MIT

At a glance

Generate a readable six-panel repository statistics infographic from validated JSON, with exact arithmetic and independent raw GitHub/Git reconciliation.

  • Tasks that involve Infographics
  • SKILL.md covers Generate, Verify accuracy and Maintain
  • Runs Python scripts from its folder; calls python and python3
  • Tasks that involve Statistics

What it does

Statistics Infographic is an agent skill from github/gh-aw, published by the product's own GitHub organization. Generate a readable six-panel repository statistics infographic from validated JSON, with exact arithmetic and independent raw GitHub/Git reconciliation.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 12 other files, including scripts and reference files (for example `examples/example.json`, `references/data-contract.md` and `scripts/audit_sources.py`).

It sits in Media & Creative, covering Infographics, Statistics and Accounting and bookkeeping. It works with GitHub and Git. The repository describes itself as: GitHub Agentic Workflows. The licence is MIT.

When your agent uses it

  • Tasks that involve Infographics
  • Tasks that involve Statistics
  • Tasks that involve Accounting and bookkeeping

Example prompts

  • “/statistics-infographic”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 9c97966. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python
    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Statistics Infographic loads about 1.3k tokens when it runs, and up to ~3.1k if it reads all its reference files. Until then it costs about 44 tokens; SKILL.md has 506 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~44
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from github/gh-aw at commit 9c97966, republished under its MIT licence (© github). 506 words, ~1,272 tokens.

Download SKILL.mdSave it as .claude/skills/statistics-infographic/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.
name
statistics-infographic
description
Generate a readable six-panel repository statistics infographic from validated JSON, with exact arithmetic and independent raw GitHub/Git reconciliation.

Repository statistics infographic

Use when asked to consolidate repository-statistics slides into one image, regenerate the infographic with updated data, or verify its calculations. This is a reusable six-panel statistical template, not an arbitrary PowerPoint screenshot collage.

The panels cover inferred PR initiation, merge/closed outcomes, start-to-merge durations, community issue outcomes, Go/JavaScript code composition, and weekly first-parent code changes. Repository names, dates, counts, proportions, and weeks come from the input, never from this skill's original dataset.

Generate

Prefer already collected source evidence. Do not fetch repository data, trigger workflows, or invent missing statistics. Keep raw data and generated images out of the repository. Use a temporary or session artifact directory.

Create a Python 3.9+ virtual environment and install the runtime manifest:

bash
python3 -m venv /tmp/statistics-infographic-venv
/tmp/statistics-infographic-venv/bin/python -m pip install \
  -r .github/skills/statistics-infographic/requirements.txt

Supply either one JSON object following examples/example.json, or a directory of existing summaries:

bash
/tmp/statistics-infographic-venv/bin/python \
  .github/skills/statistics-infographic/scripts/render_infographic.py \
  --input .github/skills/statistics-infographic/examples/example.json \
  --output /tmp/statistics-infographic.png

For real data, replace --input with --data-dir /path/to/summaries. See references/data-contract.md for schemas and statistical definitions. The example is explicitly synthetic, not a gh-aw report.

Optional arguments: --title, --font-regular, and --font-bold. Supply both font paths together. Automatic discovery supports Arial on macOS/Windows and Liberation Sans or DejaVu Sans on Linux. Missing fonts fail explicitly; no bitmap fallback is used.

The output is a static, RGB, 2560 x 3200 PNG with 300-DPI metadata. A successful render atomically replaces the explicit output path. Invalid data, unreadable layout, or invalid fonts leave an existing output intact. Counts too large for their slots, more than 10 duration bands, or more than 260 weeks require a different layout; do not silently truncate, rescale text to illegibility, or aggregate data.

Show full SKILL.md (251 more words)Show less

Verify accuracy

Input validation proves internal reconciliation, not correctness of the evidence. When cached raw API records are available, independently recompute the displayed statistics before delivery:

bash
/tmp/statistics-infographic-venv/bin/python \
  .github/skills/statistics-infographic/scripts/audit_sources.py \
  --data-dir /path/to/summaries \
  --raw-dir /path/to/raw-records \
  --repo /path/to/local-checkout

The auditor also accepts --input instead of --data-dir. Omit --repo only if local Git evidence is unavailable, and disclose that code/history were not audited. For a repository migration, explicitly supply a repeatable --repository-alias previous-owner/previous-name only when issue numbering is known to be shared.

The Git audit reads immutable objects at the full input commit, not the worktree. It requires complete local history, disables lazy object fetching, and never requests credentials or performs network operations. Missing objects or shallow history fail explicitly. Large repositories may require substantial memory for the batched blob inventory.

Open the resulting image and inspect all six panels at normal viewing size: titles, axes, labels, footnotes, chart proportions, and snapshot metadata. Automated text-bound and overlap checks complement but do not replace visual inspection.

Deliver the image with its path and disclose missing independent checks or evidence limitations. In particular, inferred source issues do not prove who initiated an agent session or which device they used. The no-issue human assumption must be explicitly authorized for the dataset.

Maintain

Install the development manifest only for validation work:

bash
/tmp/statistics-infographic-venv/bin/python -m pip install \
  -r .github/skills/statistics-infographic/requirements-dev.txt
HYPOTHESIS_STORAGE_DIRECTORY=/tmp/statistics-infographic-hypothesis \
  /tmp/statistics-infographic-venv/bin/python -m unittest discover \
  -s .github/skills/statistics-infographic/tests -v
/tmp/statistics-infographic-venv/bin/python -m mypy --strict \
  .github/skills/statistics-infographic/scripts

The implementation uses immutable typed records, explicit invariants, exact rational count ratios with half-up rounding, Decimal-oracle property tests, source-mutation regressions, deterministic rendering, safe CLI output tests, and pinned-object Git fixtures. These are rigorous software checks, not a mathematical proof of the whole program or of causal attribution.

© github, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 8 other files (scripts, references) in .github/skills/statistics-infographic of github/gh-aw.

  • SKILL.md
  • examples/example.json
  • references/data-contract.md
  • requirements-dev.txt
  • requirements.txt
  • scripts/audit_sources.py
  • scripts/render_infographic.py
  • scripts/statistics_data.py
  • tests/test_statistics.py

Open the folder on GitHubat commit 9c97966

Compare with similar skills

Statistics Infographic next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Statistics Infographic compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Statistics Infographic this skillgithub/gh-aw5.4k—~1.3kAutomated safety check: PassMIT
Book Publisherdmccreary/ibook-skills105—~1.3kAutomated safety check: PassCC-BY-NC-4.0
Procedural Fish Rendervibe-motion/skills1.3k—~419Automated safety check: PassNone
Microsim Generatordmccreary/ibook-skills105—~11kAutomated safety check: PassNone
Cs GitHub PushChenShuo2004/cs-skills194—~421Automated safety check: PassMIT
Opencharttryopendata/skills142—~11kAutomated safety check: PassMIT

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Works with

Categories

Questions about Statistics Infographic

What does Statistics Infographic do?

Generate a readable six-panel repository statistics infographic from validated JSON, with exact arithmetic and independent raw GitHub/Git reconciliation. Statistics Infographic is an agent skill from github/gh-aw, published by the product's own GitHub organization. Generate a readable six-panel repository statistics infographic from validated JSON, with exact arithmetic and independent raw GitHub/Git reconciliation.

When should I use Statistics Infographic?

Statistics Infographic fits situations like: tasks that involve Infographics; tasks that involve Statistics; tasks that involve Accounting and bookkeeping.

How do I install Statistics Infographic in Claude Code?

Run `npx skills add github/gh-aw --skill statistics-infographic -a claude-code`. Or copy the skill folder (.github/skills/statistics-infographic in github/gh-aw) into .claude/skills/statistics-infographic in your project. Claude Code loads it when a task matches its description.

How do I install Statistics Infographic in Codex?

Run `npx skills add github/gh-aw --skill statistics-infographic -a codex`. Or copy the skill folder (.github/skills/statistics-infographic in github/gh-aw) into .agents/skills/statistics-infographic in your project. Codex loads it when a task matches its description.

Can I use Statistics Infographic in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add github/gh-aw --skill statistics-infographic -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/statistics-infographic, .gemini/skills/statistics-infographic, .github/skills/statistics-infographic and .opencode/skills/statistics-infographic in your project.

What does Statistics Infographic need to run?

Going by SKILL.md and its folder, Statistics Infographic needs Python for the scripts in its folder and the command-line tools its instructions call (python and python3). Our summary lists: Python 3.

Does Statistics Infographic access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Statistics Infographic safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Statistics Infographic use?

Statistics Infographic is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Statistics Infographic use?

About 1.3k tokens (SKILL.md is roughly 5.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.8k tokens, read only when the agent opens those files.

What are the alternatives to Statistics Infographic?

Skills that share tags, products or a category with Statistics Infographic: Book Publisher (dmccreary/ibook-skills, 105 stars), Procedural Fish Render (vibe-motion/skills, 1.3k stars), Microsim Generator (dmccreary/ibook-skills, 105 stars) and Cs GitHub Push (ChenShuo2004/cs-skills, 194 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Statistics Infographic?

github (a GitHub organization, an official publisher) maintains it in github/gh-aw, which has 5,369 GitHub stars. The repository holds 53 skills in this directory. The repository was last updated on October 9, 2026.

Source: github/gh-aw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.