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 open-octo/octo-agent --skill route-optimizationgit clone --depth 1 https://github.com/open-octo/octo-agentWrote 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/open-octo/octo-agent/route-optimization)<a href="https://agentmods.dev/skills/open-octo/octo-agent/route-optimization"><img src="https://agentmods.dev/badge/skills/open-octo/octo-agent/route-optimization/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/open-octo/octo-agent/route-optimization"><img src="https://agentmods.dev/badge/skills/open-octo/octo-agent/route-optimization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00110 | $0.01085 |
| Opus 5 | $0.00055 | $0.00543 |
| Sonnet 5 | $0.00022 | $0.00217 |
| Haiku 4.5 | $0.00011 | $0.00109 |
Grade A, and why
route-optimization 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
Skill: route-optimization
行程不是"这几天分别去哪"，是"怎么走最顺、最不浪费时间"。这个技能负责研究 目的地的景点，按地理位置和开放时间设计逐日路线，每条推荐都附上理由。
景点分级
把研究到的景点按下面四类分级，而不是笼统地列一堆"推荐去的地方"：
| 分级 | 说明 |
|---|---|
| 必去 | 标志性、普遍推荐、代表这个目的地 |
| 推荐 | 评价很高但不是必去 |
| 可选 | 小众兴趣，时间充裕的话值得去 |
| 踩雷预警 | 名气大但被高估/性价比低（说明为什么） |
每个景点要有的实用信息
- 开放时间和闭馆日
- 门票价格和购票渠道（优先官方链接）
- 最佳游览时段（上午vs下午、工作日vs周末）
- 预计游览时长
- 无障碍设施说明（如果相关）
路线优化原则
设计逐日路线时：
- 地理就近分组：同一天安排地理位置相近的景点，减少往返路程。
- 兼顾开放时间：不要把闭馆日安排上，也不要让路线依赖某个景点的 特定开放窗口却没留够时间。
- 松紧搭配：一天高强度游览之后，安排一天相对轻松的内容，不要连续 排满高强度行程。
- 人群构成适配：带娃的行程要考虑儿童友好度和体力消耗；商务/独自 出行可以排更紧凑的节奏。
季节感知
针对具体的出行月份，说明：
- 当季的节庆、活动、特展
- 天气对户外行程的影响
- 旺季/淡季的人流差异
- 只有这个季节才有的体验（不要放到淡季安排里）
拍照点位
如果用户对摄影感兴趣，标出：
- 最佳光线的时间段
- 具体的取景点位
- 当月的日出日落时间
周边一日游
研究从落脚城市出发可行的一日游：
- 交通方式和耗时
- 值不值得去的判断
- 是全天还是半天行程
输出要求
- 每条推荐都要附理由——不能只列"去这个地方"，要说明"为什么推荐这个"。
- 引用信息来源（有网址的附网址）。
- 用用户指定的语言输出。
- 考虑用户说明的人群构成（比如家庭出行要标注哪些活动对儿童友好）和 兴趣、节奏偏好。
和其他技能的配合
预算相关的细节（门票价格加总、每日预算分配）交给 budget-allocation，
这个技能只负责路线本身，不做费用汇总。
边界
- 不臆造具体的开放时间/票价——这类信息时效性强，用
web_search/web_fetch实际检索确认，检索不到就明确说"建议出行前再核实一次"， 不要凭训练知识里的印象给出可能已经过时的具体数字。 - 不忽略用户说明的约束（预算、体力、带娃）硬塞一个"标准最优路线"—— 路线要适配这次出行的实际情况。
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 94 lines · 110 tokens per session scan A a2eab151dc4b
route-optimization is a skill published in the GitHub repository open-octo/octo-agent (97 stars, last pushed yesterday), licensed MIT. It adds 110 tokens to every session and 1,085 once invoked, about $0.0006 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.
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