Token Dashboard logo

Token Dashboard

CommunityPopular
alexgreensh
token-dashboard

Open the Token Optimizer dashboard in your browser (context usage, quality, savings). Use to view the dashboard.

Overview

Publisheralexgreensh
Repositorytoken-optimizer
Skill nametoken-dashboard
Stars
2.5K
Forks
193
Bundled files
Instructions only
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 alexgreensh on GitHub. Read the source before you install it.

Installation

Install the Token Dashboard 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.
    https://github.com/alexgreensh/token-optimizer/tree/main/cowork/token-optimizer/skills/token-dashboard
  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/alexgreensh/token-optimizer.git /tmp/token-optimizer
mkdir -p .claude/skills
cp -r /tmp/token-optimizer/cowork/token-optimizer/skills/token-dashboard .claude/skills/token-dashboard
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Token Dashboard 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 Token Dashboard 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 Token Dashboard 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.

Token Optimizer Dashboard

Opens an up-to-date dashboard showing your context usage trends, quality scores, session history, and skill management.

Instructions

  1. Resolve runtime and measure.py path:
bash
RUNTIME="${TOKEN_OPTIMIZER_RUNTIME:-}"
if [ -z "$RUNTIME" ]; then
  if [ -n "$CLAUDE_PLUGIN_ROOT" ] || [ -n "$CLAUDE_PLUGIN_DATA" ]; then
    RUNTIME="claude"
  elif [ -n "$OPENCODE" ] || [ -n "$OPENCODE_BIN" ] || [ -n "$OPENCODE_CONFIG_DIR" ] || [ -n "$OPENCODE_CONFIG" ]; then
    RUNTIME="opencode"
  elif [ -n "$CODEX_HOME" ]; then
    RUNTIME="codex"
  elif [ -n "$CLAUDECODE" ] || [ -n "$CLAUDE_CODE_ENTRYPOINT" ] || [ -n "$CLAUDE_CODE_SESSION_ID" ]; then
    RUNTIME="claude"
  elif [ -d "$HOME/.config/opencode" ] && [ ! -d "$HOME/.codex" ]; then
    RUNTIME="opencode"
  elif [ -d "$HOME/.codex" ]; then
    RUNTIME="codex"
  else
    RUNTIME="claude"
  fi
fi

# Resolve measure.py to the NEWEST installed copy across channels so a stale
# plugin-cache copy never shadows a fresh install. find -L follows the
# install.sh symlink under ~/.claude/skills; cd -P resolves it before reading each
# copy's plugin.json for its version. find (not bare globs) never errors under zsh.
MEASURE_PY=""; _best_ver=""
while IFS= read -r _cand; do
  [ -f "$_cand" ] || continue
  _root="$(cd -P -- "$(dirname -- "$_cand")/../../.." 2>/dev/null && pwd)"
  _ver="$(sed -n 's/.*"version"[[:space:]]*:[[:space:]]*"\([^"]*\)".*/\1/p' "$_root/.claude-plugin/plugin.json" 2>/dev/null | head -1)"
  [ -n "$_ver" ] || _ver="0.0.0"
  if [ -z "$_best_ver" ] || [ "$(printf '%s\n%s\n' "$_ver" "$_best_ver" | sort -t. -k1,1n -k2,2n -k3,3n -k4,4n | tail -n1)" = "$_ver" ]; then
    _best_ver="$_ver"; MEASURE_PY="$_cand"
  fi
done <<EOF
$(find -L "$HOME/.claude/skills" "$HOME/.claude/plugins/cache" "$HOME/.claude/token-optimizer" "$HOME/.codex/skills" "$HOME/.codex/plugins/cache" "$HOME/.config/opencode/plugins/cache" "$HOME/.config/opencode/plugins" -type f -name measure.py -path '*token-optimizer*/scripts/measure.py' 2>/dev/null)
EOF
if [ -z "$MEASURE_PY" ]; then echo "[Error] measure.py not found. Is Token Optimizer installed?"; exit 1; fi
export TOKEN_OPTIMIZER_RUNTIME="$RUNTIME"
  1. Collect and open:
bash
# TOKEN_OPTIMIZER_INTERACTIVE=1 marks this as a user-initiated open so the 20s
# hook budget does NOT kill a heavy rebuild (Bug B: on a large history the
# dashboard would otherwise be skipped and served stale). The user is actively
# waiting for this open, so it runs unbounded.
TOKEN_OPTIMIZER_INTERACTIVE=1 python3 "$MEASURE_PY" collect --quiet && \
  TOKEN_OPTIMIZER_INTERACTIVE=1 python3 "$MEASURE_PY" dashboard

This collects the latest session data into the trends database, regenerates the dashboard HTML, and opens it in your default browser.

  1. Tell the user the dashboard is open. Probe the daemon BEFORE mentioning any URL (v5.3.3+):
    • Probe daemon: python3 "$MEASURE_PY" daemon-status 2>/dev/null
    • If DAEMON_RUNNING: lead with URL: http://localhost:24842/token-optimizer (bookmarkable, auto-updates), then mention the file fallback.
    • If DAEMON_NOT_RUNNING: do NOT print the localhost:24842 URL. Tell the user the dashboard opened as a file, and suggest python3 $MEASURE_PY setup-daemon (macOS and Windows) if they want a bookmarkable URL.
    • File path: never hardcode it. It is install-dependent. Cite the Dashboard: line from the step-2 output.
    • For Codex when DAEMON_NOT_RUNNING: do not imply the Claude daemon is required; the generated file works, and Stop hooks refresh it when balanced hooks are installed.

Frequently asked questions

What does the Token Dashboard AI skill do?

Open the Token Optimizer dashboard in your browser (context usage, quality, savings). Use to view the dashboard.

Why use Token Dashboard on TypingMind?

Because you install it once and use it with any model. Token Dashboard 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 Token Dashboard in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/alexgreensh/token-optimizer/tree/main/cowork/token-optimizer/skills/token-dashboard. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Token Dashboard?

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 Token Dashboard?

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

Is the Token Dashboard AI skill free?

It is published on GitHub by alexgreensh. Check the repository for licensing terms. 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇