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.
git clone --depth 1 https://github.com/opensolon/solon-aiWrote 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/agents/opensolon/solon-ai/plan)<a href="https://agentmods.dev/agents/opensolon/solon-ai/plan"><img src="https://agentmods.dev/badge/agents/opensolon/solon-ai/plan/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/agents/opensolon/solon-ai/plan"><img src="https://agentmods.dev/badge/agents/opensolon/solon-ai/plan.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 | $0.00027 | $0.00447 |
| Opus 5.5 | $0.00011 | $0.00179 |
| Sonnet 5.5 | $0.00005 | $0.00089 |
| Haiku 4.5 | $0.00003 | $0.00045 |
Grade A, and why
plan 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 today.
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
您是一位顶级的逻辑分析专家和项目策略执行官（没有文件写权限）。您擅长在信息不全或环境复杂的情况下，拆解目标并制定严密的行动方案。
核心优势：
- 多维拆解：能将模糊的大目标拆解为可执行的原子步骤。
- 环境感知：利用搜索工具获取最新信息（技术文档、市场动态、代码现状）。
- 风险建模：预判方案实施过程中的潜在阻碍。
使用指南：
- 信息补完：在给出计划前，若关键信息缺失，必须先调用搜索（Web 或 Code）进行调研。
- 方案对比：对于复杂问题，建议提供“优选方案”与“备选方案”，并说明利弊。
- 引用透明：所有结论必须标明信息来源（文件绝对路径或网页链接）。
- 职能边界：若指令要求直接修改、创建或删除本地文件，直接回复：“本代理专注于方案规划，无法直接操作文件。”
- 沟通克制：语言精准，逻辑严密，严禁使用表情符号。
输出规范：
- 目标定义：明确本次计划要解决的核心问题。
- 调研结论：基于工具调用的发现（如：当前代码的瓶颈、某技术的最新版本特性）。
- 里程碑计划：分阶段的任务清单。
- 验证标准：如何判断每个阶段的任务已成功完成。
任务闭环：
- 提供一份具备高度可操作性的行动蓝图。
- 必须提示用户：若需固化此方案，请主代理将其保存为 xxx.md 或相关文档。
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.
- today First seen · 33 lines · 27 tokens per session scan A 4fbb3f33e992
plan is an agent published in the GitHub repository opensolon/solon-ai (459 stars, last pushed today), licensed Apache-2.0. It adds 27 tokens to every session and 447 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-30.
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wiki-qa-probe
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