Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add lisihao/Solar --skill statsgit clone --depth 1 https://github.com/lisihao/SolarWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/lisihao/solar/stats)<a href="https://agentmods.dev/skills/lisihao/solar/stats"><img src="https://agentmods.dev/badge/skills/lisihao/solar/stats/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/lisihao/solar/stats"><img src="https://agentmods.dev/badge/skills/lisihao/solar/stats.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00011 | $0.00653 |
| Opus 5 | $0.00005 | $0.00327 |
| Sonnet 5 | $0.00002 | $0.00131 |
| Haiku 4.5 | $0.00001 | $0.00065 |
Grade A, and why
stats scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
/stats - Solar 使用统计
功能
显示当前会话的 Token 使用情况和 Rate Limit 状态。
显示格式
执行 /stats 时,显示以下面板:
╔══════════════════════════════════════════════════════════╗
║ 📊 Solar 使用统计 ║
╠══════════════════════════════════════════════════════════╣
║ ║
║ 💬 当前会话 ║
║ ├─ 输入 Token: 12,345 ║
║ ├─ 输出 Token: 8,234 ║
║ ├─ 总计: 20,579 ║
║ └─ 预估费用: $0.12 ║
║ ║
║ ⏱️ Rate Limit (5小时窗口) ║
║ ├─ 已使用: 45,000 / 88,000 (51%) ║
║ ├─ 剩余: 43,000 ║
║ ├─ 重置时间: 2小时34分钟后 ║
║ └─ 状态: 🟢 正常 ║
║ ║
║ 📈 本次对话 ║
║ ├─ 消息数: 15 ║
║ ├─ 工具调用: 23 ║
║ └─ Agent 调用: 3 ║
║ ║
╚══════════════════════════════════════════════════════════╝
数据来源
使用 Claude Code 内置命令获取数据:
# Token 使用详情
/context
# 使用统计
/usage
# 费用统计
/cost
Rate Limit 状态指示
| 状态 | 使用比例 | 建议 |
|---|---|---|
| 🟢 正常 | < 50% | 可继续正常使用 |
| 🟡 注意 | 50-80% | 考虑精简操作 |
| 🔴 警告 | > 80% | 建议 /save 并暂停 |
自动提醒
当 Rate Limit 超过 80% 时,自动提示:
⚠️ Rate Limit 警告
─────────────────
已使用: 85%
建议: 执行 /save 保存会话状态,稍后继续
与其他命令的关系
| 命令 | 功能 |
|---|---|
/stats |
Solar 统计面板 (本命令) |
/context |
Claude Code 内置 - 详细 token 分解 |
/usage |
Claude Code 内置 - 使用限制 |
/cost |
Claude Code 内置 - 费用统计 |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 86 lines · 11 tokens per session scan A fb2c1d6e8f47
stats is a skill published in the GitHub repository lisihao/Solar (2 stars, last pushed 28d ago), licensed MIT. It adds 11 tokens to every session and 653 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…