Tokdash: Agent Dashboard: Visualization and analytics for Sessions and Quota Usage

by JingbiaoMei · Codex Skill · ★ 87

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install Tokdash

pip install tokdash
pip install --upgrade tokdash

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 75/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

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Quick Facts

Stars87
Forks21
LanguagePython
CategoryCodex Skill
LicenseMIT
Quality Score75/100
Open Issues7
Last Updated2026-10-18
Created2026-02-24
Platformsclaude-code, cli, codex, python
Est. Tokens~17k

About Tokdash

English &nbsp;|&nbsp; 中文 Local token &amp; cost dashboard for AI coding tools <img src="https://raw.git

Tokdash alternative? Top 6 similar tools

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  • toktrack by mag123c · ⭐ 196

    Ultra-fast token & cost tracker for LLM Token Usage (e.g. Claude Code)

  • vibepod-cli by VibePod · ⭐ 180

    Unified CLI for running AI coding agents in isolated containers. Includes built-in local metrics collection, H

  • remindb by radimsem · ⭐ 129

    An agentic memory database that cuts session tokens by 82–99%. One portable SQLite file — your agent's memory,

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

View on GitHub → Browse Codex Skill tools