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 agentgit 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/agent)<a href="https://agentmods.dev/skills/lisihao/solar/agent"><img src="https://agentmods.dev/badge/skills/lisihao/solar/agent/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/agent"><img src="https://agentmods.dev/badge/skills/lisihao/solar/agent.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 | $0.00016 | $0.00611 |
| Opus 5.5 | $0.00006 | $0.00244 |
| Sonnet 5.5 | $0.00003 | $0.00122 |
| Haiku 4.5 | $0.00002 | $0.00061 |
Grade A, and why
agent 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 1mo 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.
This is a copy
86% identical to multi-agent-design — 152 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
/agent - Agent 选择器
功能
列出可用的 Solar Agent，或激活指定 Agent。
使用方式
/agent # 列出所有可用 Agent
/agent Researcher # 激活 Researcher
@Researcher # 快捷方式 (等同于 /agent Researcher)
可用 Agent 列表
当用户输入 /agent 或 @ 时，显示：
═══════════════════════════════════════════════════
🌟 Solar Agent 列表
═══════════════════════════════════════════════════
📊 决策层 (Opus)
@Researcher - 技术调研、可行性分析
@Architect - 架构设计、技术评审
@PM - 产品验收、竞争力评估
⚡ 执行层 (Sonnet)
@Coder - 代码实现、重构
@Tester - 测试编写、执行
@Reviewer - 代码审查、安全检查
@Secretary - 记录整理、Agent评估
🔧 支撑层
@Docs - 文档生成 (Sonnet)
@Ops - 构建部署 (Sonnet)
@Guard - 规范检查 (Haiku)
═══════════════════════════════════════════════════
用法: @Agent名称 + 你的请求
示例: @Researcher 调研 SIMD 向量化优化技术
═══════════════════════════════════════════════════
Agent 激活逻辑
当用户指定 Agent 时：
- 验证 Agent 名称 - 检查是否在列表中
- 加载 Agent 定义 - 读取
agents/{name}.md - 切换上下文 - 按该 Agent 的角色和约束执行
- 标记输出 - 响应前标注当前 Agent
输出标记
激活 Agent 后，响应格式：
[@Researcher]
─────────────
{Agent 的响应内容}
@ 语法识别规则
以下模式应被识别为 Agent 调用：
@Solar- 使用完整 Solar 流程@Researcher- 单独调用 Researcher@Architect- 单独调用 Architect@Coder- 单独调用 Coder- ... (所有 Agent)
注意事项
- 单独调用 Agent 会跳过 Solar 的阶段流程
- 如需完整流程，使用
@Solar或不指定 Agent - Agent 名称不区分大小写
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.
- 1mo ago First seen · 88 lines · 16 tokens per session scan A 9da5490c1677
agent is a skill published in the GitHub repository lisihao/Solar (3 stars, last pushed 2mo ago), licensed MIT. It adds 16 tokens to every session and 611 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 86% identical to multi-agent-design, differing in 152 lines, and is treated as a copy.
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