price-list

price-list is a skill for Claude Code, Codex from EverMind-AI/Raven. It costs 67 tokens per session (802 once invoked), scanned A, original, Apache-2.0.

A reference price list for Hai Lan Travel packages, with prices by group size and travel season. It also lists extra costs such as added nights, insurance, station transfers, and seat upgrades.

In plain words
What is it for?
It helps prepare package quotes, compare the Economy, Comfort, and Custom options, and calculate add-ons for a booking.
Why use it?
It gives the agent a fixed source for calculating quotes instead of guessing prices or applying inconsistent rules. It also clarifies how season, group size, children, and room sharing affect the total.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It helps prepare package quotes, compare the Economy, Comfort, and Custom options, and calculate add-ons for a booking.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/evermind-ai/raven/price-list
About the project

Raven is an open-source agent harness for running long-term AI work with terminal execution, tracing, memory, skills, evaluation, and reusable workflows. People use the current release to operate and improve persistent AI workflows, while its described future direction is a multi-agent system that combines specialized harnesses.

EverMind-AI/Raven · 5,497 stars · on GitHub · raven.evermind.ai

Install

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.

Any agent
npx skills add EverMind-AI/Raven --skill price-list
Clone the repo
git clone --depth 1 https://github.com/EverMind-AI/Raven

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for price-list

README.md
[![agentmods](https://agentmods.dev/badge/skills/evermind-ai/raven/price-list/github.svg)](https://agentmods.dev/skills/evermind-ai/raven/price-list)
Your own site
<a href="https://agentmods.dev/skills/evermind-ai/raven/price-list"><img src="https://agentmods.dev/badge/skills/evermind-ai/raven/price-list/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.

agentmods 80×15 button for price-list

Your own site · 80×15
<a href="https://agentmods.dev/skills/evermind-ai/raven/price-list"><img src="https://agentmods.dev/badge/skills/evermind-ai/raven/price-list.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 67 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 802 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00067 $0.00802
Opus 5.5 $0.00027 $0.00321
Sonnet 5.5 $0.00013 $0.00160
Haiku 4.5 $0.00007 $0.00080

Measured 21d ago against content hash d40cb2bfdc67, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

price-list 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 21d 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.

experimental/simulation/scenarios/travel_agency/materials/price-list/SKILL.md · 62 lines

What it actually says

海岚旅行价目表(现行)

文件编号 HL-FIN-PRC-06,V3.1,2026年9月15日起执行。

计价规则

  • 价格为每人基础价,单位人民币元,含对应产品说明列出的内容,含出发城市往返大交通;全国出发城市同价。
  • 季节档按出发日期所在档确定;人数档按全团总人数(含儿童)确定。
  • 住宿按两人一间安排;奇数人数安排三人间或加床,不另收房差;1人出行按"1人"档计价。儿童价为占床价。
  • 儿童价、预付款、退改规则见预订规则 HL-CS-POL-02。

季节档

档 日期
淡季 11月16日至次年2月底(春节期间除外)
平季 3月1日至6月30日;9月1日至9月30日;10月8日至11月15日
旺季 7月1日至8月31日;10月1日至10月7日;春节期间(具体日期以同事确认为准)

经济游(基础3晚)

人数 淡季 平季 旺季
1人 1,180 1,280 1,380
2至3人 820 900 980
4至8人 760 800 900

加一晚:每人每晚 260。

舒适游(基础4晚)

人数 淡季 平季 旺季
1人 4,300 4,800 5,600
2至3人 3,500 3,900 4,600
4至8人 3,200 3,600 4,200

加一晚:每人每晚 800。套房升级:每间每晚 600。

定制游(基础5晚,起价)

人数 淡季 平季 旺季
1人 19,000 21,000 24,000
2人 15,000 16,500 19,000
3至6人 13,500 14,800 17,000

加一晚:每人每晚 2,600。加一天私人向导:每团每天 1,500。定制游价格为起价,最终价格以规划通话确定。

附加项

附加项 价格 适用
旅游意外险 每人 60 各产品,自愿购买
高铁一等座升级 每人每程 120 仅经济游
接送站 每团每程 150 经济游可加购;舒适游、定制游已含
Changes

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.

  1. 21d ago First seen · 62 lines · 67 tokens per session scan A d40cb2bfdc67

Subscribe to this mod's changes

price-list is a skill published in the GitHub repository EverMind-AI/Raven (5,497 stars, last pushed today), licensed Apache-2.0. It adds 67 tokens to every session and 802 once invoked, about $0.0003 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 2026-09-27.