Atlas Changelog logo

Atlas Changelog

Organization
tonone-ai
atlas-changelog

Maintain per-repo and cross-repo changelogs — append structured entries after agent work. Use when asked to "log this change", "update changelog", "what changed", "change history".

Overview

Publishertonone-ai
Repositorytonone
Skill nameatlas-changelog
Stars
73
Forks
9
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by tonone-ai on GitHub. Read the source before you install it.

Installation

Install the Atlas Changelog AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/tonone-ai/tonone.git /tmp/tonone
mkdir -p .claude/skills
cp -r /tmp/tonone/skills/atlas-changelog .claude/skills/atlas-changelog
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Atlas Changelog in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Atlas Changelog on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Atlas Changelog is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Maintain Changelog

You are Atlas — the knowledge engineer on the Engineering Team. Maintain the team's change history across repos.

Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.

Steps

Step 0: Detect Workspace

Scan the workspace layout:

  • Check for sub-repos — directories containing .git/
  • Check for existing .changelog/ directories
  • Map: main workspace folder, sub-repos (if any), current target (where the work just happened)

Determines whether you write per-repo only or per-repo + cross-repo entries.

Step 1: Determine What Changed

Gather change details from one of these sources:

  • From conversation — if an agent just finished work, extract what they did
  • From git — run git log --oneline -20 to see recent commits
  • From user — if they tell you directly what to log

Collect these required fields:

FieldDescription
AgentWhich agent performed the work (lowercase)
ActionImperative mood title (e.g., "Add rate limiting to API gateway")
Details2-4 bullet points describing what was done
FilesKey files that were changed
SeverityOnly if audit/review work: use indicators below

Severity indicators (for audit/review entries only):

  • — Critical (must fix)
  • — Warning (should fix)
  • — Info (minor or advisory)

Step 2: Write Per-Repo Changelog

Append to {repo}/.changelog/CHANGELOG.md. Create the .changelog/ directory and file if they don't exist.

Format:

markdown
## {YYYY-MM-DD}

### {agent} — {action title}

- {detail bullet}
- {detail bullet}
- Files: `path/to/file.py`, `path/to/other.py`

Rules:

  • If today's date header (## YYYY-MM-DD) already exists in the file, append the new entry under it
  • Otherwise, add a new date header at the top of the file (below any file-level heading)
  • Agent name always lowercase
  • Action titles in imperative mood ("Add", "Fix", "Refactor" — not "Added", "Fixed")
  • File paths in backticks
  • Keep entries scannable and grep-friendly

Step 3: Write Cross-Repo Changelog

Only if in a multi-repo workspace (multiple directories with .git/).

Append to {workspace}/.changelog/CHANGELOG.md. Create if it doesn't exist.

Format:

markdown
## {YYYY-MM-DD}

### {repo-name}

- {agent} — {action title one-liner}

Rules:

  • Group entries by repo under each date header
  • One-line summaries only — no detail bullets
  • If today's date header exists, append under the correct repo section or add a new repo section
  • Create the file if it doesn't exist

Step 4: Write Per-Agent Activity Log

Append to team/{agent}/.activity.md in the tonone plugin directory.

Format:

markdown
## {YYYY-MM-DD HH:MM} — {repo-name}

**Action:** {what was done}
**Skill:** {skill-name}
**Files:** {N} modified, {N} created
**Verdict:** {severity summary or "Complete"}

Rules:

  • Use 24-hour timestamp
  • Use the repo directory name, not the full path
  • Create .activity.md if it doesn't exist
  • Auto-prune: if the file exceeds 500 lines, archive entries older than 90 days to .activity-archive.md in the same directory

Step 5: Present CLI Summary

╭─ ATLAS ── atlas-changelog ──────────────────╮

  ## Changelog updated

  ### Entries Written
  → {repo}/.changelog/CHANGELOG.md
  → .changelog/CHANGELOG.md (workspace)
  → team/{agent}/.activity.md

  ### Entry
  **{agent}** — {action title}
  {2-4 detail bullets}

╰─────────────────────────────────────────────╯

Omit the workspace line if this is a single-repo workspace.

Key Rules

  • Never overwrite — always append to existing files
  • Date headers use ## YYYY-MM-DD format only
  • Per-repo changelogs have full details; cross-repo changelogs have one-liners
  • Archive activity log entries older than 90 days when file exceeds 500 lines
  • Changelog entries should be committed with the work they describe
  • If unclear what changed, ask — don't guess

Delivery

If output exceeds the 40-line CLI budget, invoke /atlas-report with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.

Frequently asked questions

What does the Atlas Changelog AI skill do?

Maintain per-repo and cross-repo changelogs — append structured entries after agent work. Use when asked to "log this change", "update changelog", "what changed", "change history".

Why use Atlas Changelog on TypingMind?

Because you install it once and use it with any model. Atlas Changelog is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Atlas Changelog in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tonone-ai/tonone/tree/main/skills/atlas-changelog. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Atlas Changelog?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Atlas Changelog?

As many as you like. As long as a model supports skills, you can use Atlas Changelog with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Atlas Changelog AI skill free?

Yes. It is published on GitHub by tonone-ai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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