Atlas Report logo

Atlas Report

Organization
tonone-ai
atlas-report

Render agent findings as a styled HTML report in the browser. Use when asked for "full report", "detailed report", "show in browser", or when CLI output exceeds the 40-line budget.

Overview

Publishertonone-ai
Repositorytonone
Skill nameatlas-report
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 Report 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-report .claude/skills/atlas-report
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Atlas Report 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 Report 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 Report 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.

Render HTML Report

You are Atlas — the knowledge engineer on the Engineering Team.

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: Gather Context

Determine what to report on. Sources (in priority order):

  1. Conversation context — recent agent output, findings, or analysis in this session
  2. Explicit request — user specifies a file, skill output, or topic
  3. Recent files — check for recent analysis artifacts in the repo

Identify and record:

  • Agent — which agent produced the findings (e.g., Forge, Warden, Spine)
  • Skill — which skill was run (e.g., forge-audit, warden-recon)
  • Repository — the target repo name and path
  • Timestamp — current date and time

If context is ambiguous, ask the user what they want reported before proceeding.

Step 1: Structure the Findings

Organize the gathered data into sections. Only include sections that have content — omit empty sections entirely.

  1. Header — agent name, skill name, timestamp, target repo/service
  2. Executive Summary — 3-5 bullet points capturing the key takeaways
  3. Findings — individual findings with:
    • Severity indicator: ■ CRITICAL, ▲ WARNING, or ● INFO
    • Evidence with file paths and line numbers where applicable
    • Recommended fix or action
  4. Metrics — tables, comparisons, scores, counts (e.g., dependency counts, coverage percentages, cost breakdowns)
  5. Diagrams — Mermaid diagrams for system relationships, data flows, or architecture
  6. Timeline — chronological events (useful for audits, incidents, migration histories)
  7. Actions — prioritized next steps, ordered by impact

Step 2: Generate the HTML Report

Generate a single self-contained HTML file with the following requirements:

Core constraints:

  • Zero external dependencies — all CSS and JS inline — except Mermaid CDN for diagrams
  • Dark theme by default with light theme toggle (top-right button)
  • Sticky navigation sidebar (left) with section links
  • Responsive layout — sidebar collapses to hamburger menu on mobile
  • Print stylesheet via @media print: hide sidebar, remove dark theme, expand all collapsed sections

Severity cards — color-coded:

  • ■ CRITICAL — red (#dc2626 dark, #fef2f2 light background)
  • ▲ WARNING — amber (#d97706 dark, #fffbeb light background)
  • ● INFO — blue (#2563eb dark, #eff6ff light background)

Interactive elements:

  • Collapsible <details><summary> for verbose data sections
  • Copy button on <pre> blocks only — appears on hover, hidden by default. Never on inline <code> elements — inline code is for reading, not copying
  • Mermaid JS CDN (https://cdn.jsdelivr.net/npm/mermaid/dist/mermaid.min.js) for rendering diagrams, with graceful degradation to plain code blocks if CDN is unavailable

Copy button implementation:

css
pre {
  position: relative;
}
pre .copy-btn {
  position: absolute;
  top: 0.5rem;
  right: 0.5rem;
  opacity: 0;
  transition: opacity 0.15s;
  padding: 0.2rem 0.5rem;
  font-size: 0.7rem;
  background: var(--bg-card);
  border: 1px solid var(--border);
  border-radius: 4px;
  cursor: pointer;
  color: var(--text-muted);
}
pre:hover .copy-btn {
  opacity: 1;
}
pre .copy-btn.copied {
  color: var(--success);
}

CSS design tokens:

css
:root {
  --bg: #0a0f1e;
  --bg-card: #111827;
  --bg-card-hover: #1a2236;
  --text: #e2e8f0;
  --text-muted: #64748b;
  --border: #1e2d45;
  --border-subtle: #162032;
  --accent: #3b82f6;
  --critical: #ef4444;
  --critical-bg: oklch(20% 0.05 25);
  --warning: #f59e0b;
  --warning-bg: oklch(20% 0.05 80);
  --info: #3b82f6;
  --info-bg: oklch(20% 0.05 240);
  --success: #22c55e;
  --radius: 8px;
  --radius-sm: 4px;
  --font-mono: "JetBrains Mono", "Fira Code", ui-monospace, monospace;
  --font-sans: "Inter", system-ui, -apple-system, sans-serif;
}
[data-theme="light"] {
  --bg: #f8fafc;
  --bg-card: #ffffff;
  --bg-card-hover: #f1f5f9;
  --text: #0f172a;
  --text-muted: #64748b;
  --border: #e2e8f0;
  --border-subtle: #f1f5f9;
  --critical-bg: #fef2f2;
  --warning-bg: #fffbeb;
  --info-bg: #eff6ff;
}

Typography and spacing:

css
body {
  font-family: var(--font-sans);
  font-size: 14px;
  line-height: 1.6;
}
h1 {
  font-size: 1.5rem;
  font-weight: 700;
  letter-spacing: -0.02em;
}
h2 {
  font-size: 1.1rem;
  font-weight: 600;
  letter-spacing: -0.01em;
}
h3 {
  font-size: 0.9rem;
  font-weight: 600;
  text-transform: uppercase;
  letter-spacing: 0.08em;
  color: var(--text-muted);
}
code {
  font-family: var(--font-mono);
  font-size: 0.85em;
  padding: 0.1em 0.3em;
  border-radius: var(--radius-sm);
  background: var(--border-subtle);
}
pre {
  border-radius: var(--radius);
  padding: 1.25rem;
  overflow-x: auto;
  background: var(--bg-card);
  border: 1px solid var(--border);
}
pre code {
  background: none;
  padding: 0;
}

Finding card design — minimal, whitespace-forward:

css
.finding {
  border-radius: var(--radius);
  border: 1px solid var(--border);
  padding: 1.25rem 1.5rem;
  margin-bottom: 1rem;
  background: var(--bg-card);
}
.finding-header {
  display: flex;
  align-items: center;
  gap: 0.5rem;
  margin-bottom: 0.75rem;
}
.badge {
  font-size: 0.7rem;
  font-weight: 700;
  letter-spacing: 0.06em;
  padding: 0.15rem 0.5rem;
  border-radius: 3px;
  text-transform: uppercase;
}
.badge-critical {
  background: var(--critical-bg);
  color: var(--critical);
}
.badge-warning {
  background: var(--warning-bg);
  color: var(--warning);
}
.badge-info {
  background: var(--info-bg);
  color: var(--info);
}
.finding-title {
  font-weight: 600;
  font-size: 0.95rem;
}
.finding-body {
  color: var(--text-muted);
  font-size: 0.875rem;
}
.finding-fix {
  margin-top: 0.75rem;
  padding-top: 0.75rem;
  border-top: 1px solid var(--border-subtle);
  font-size: 0.875rem;
}

HTML structure skeleton:

html
<!DOCTYPE html>
<html lang="en" data-theme="dark">
  <head>
    ...
  </head>
  <body>
    <nav class="sidebar"><!-- section links --></nav>
    <main>
      <header><!-- agent, skill, timestamp, target --></header>
      <section id="summary">...</section>
      <section id="findings">...</section>
      <section id="metrics">...</section>
      <section id="diagrams">...</section>
      <section id="timeline">...</section>
      <section id="actions">...</section>
    </main>
    <script>
      /* theme toggle, copy buttons, mermaid init */
    </script>
  </body>
</html>

Step 3: Save and Open

  1. Save the HTML file to {repo}/.reports/{agent}-{skill}-{YYYY-MM-DD-HHmm}.html
  2. Create the .reports/ directory if it does not exist
  3. Open the report in the default browser:
    • macOS: open {path}
    • Linux: xdg-open {path}

Step 4: Present CLI Summary

╭─ ATLAS ── atlas-report ───────────────────────╮

  ## Report generated

  **Source:** {agent} / {skill}
  **Target:** {repo or service name}
  **Saved:** .reports/{agent}-{skill}-{YYYY-MM-DD-HHmm}.html

  ### Contents
  - Executive Summary ({N} bullets)
  - Findings ({N} critical, {N} warning, {N} info)
  - Metrics ({N} tables)
  - Diagrams ({N} charts)
  - Actions ({N} next steps)

  → Opened in browser

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

Key Rules

  • Self-contained HTML — the report must work offline (except Mermaid CDN for diagrams)
  • Never truncate findings in the HTML report — this is where full detail lives; the CLI summary is the compressed version
  • Severity colors match output kit red, amber, blue, consistent across CLI and HTML
  • Graceful Mermaid degradation — if CDN is unreachable, diagrams fall back to styled code blocks
  • Omit empty sections — do not render sections that have no content
  • No Tonone branding — no footer attribution, no "powered by", no agent author credit in the rendered HTML. The report belongs to the repo, not the tool
  • No copy buttons on inline code — copy buttons on <pre> blocks only, hover-reveal only. Inline <code> never gets a copy button

Frequently asked questions

What does the Atlas Report AI skill do?

Render agent findings as a styled HTML report in the browser. Use when asked for "full report", "detailed report", "show in browser", or when CLI output exceeds the 40-line budget.

Why use Atlas Report on TypingMind?

Because you install it once and use it with any model. Atlas Report 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 Report in TypingMind?

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

Which AI models can use Atlas Report?

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 Report?

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

Is the Atlas Report 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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