cost-xray: See what Claude Code and Codex actually send to the API — and what each part costs

by tigerless-labs · Codex Skill · ★ 5.8k

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

Security audit verdict: SAFE · quality 73/100

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

Stars5,825
Forks375
LanguagePython
CategoryCodex Skill
LicenseMIT
Quality Score73/100
Open Issues14
Last Updated2026-11-02
Created2026-06-06
Platformsclaude-code, cli, codex, python
Est. Tokens~16k

About cost-xray

cost-xray See what your AI coding agent actually sends to the API — and what each part costs. Most usage tools read local logs. That shows the total cost of a call or session, but it misses the request-time context assembled before the model is invoked: system prompts, tool schemas, MCP blocks, tool results, cache reads/writes, and previous thinking blocks.

cost-xray alternative? Top 6 similar tools

Looking for a cost-xray alternative? If you're comparing cost-xray with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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    Orchestrate Claude, Codex and Grok in one app. Open-source (MIT), reuses the subscriptions you already pay for

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  • claude-scholar by Galaxy-Dawn · ⭐ 5.8k

    Semi-automated research assistant for academic research and software development. Supports Claude Code, Codex

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  • antigravity-claude-proxy by badrisnarayanan · ⭐ 4.0k

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  • ralph-orchestrator by mikeyobrien · ⭐ 3.2k

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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