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 ssmurfgg04-gif/context-m --skill dream-interpretergit clone --depth 1 https://github.com/ssmurfgg04-gif/context-mWrote 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/ssmurfgg04-gif/context-m/dream-interpreter)<a href="https://agentmods.dev/skills/ssmurfgg04-gif/context-m/dream-interpreter"><img src="https://agentmods.dev/badge/skills/ssmurfgg04-gif/context-m/dream-interpreter/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/ssmurfgg04-gif/context-m/dream-interpreter"><img src="https://agentmods.dev/badge/skills/ssmurfgg04-gif/context-m/dream-interpreter.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 | $0.00062 | $0.00871 |
| Opus 5 | $0.00031 | $0.00436 |
| Sonnet 5 | $0.00012 | $0.00174 |
| Haiku 4.5 | $0.00006 | $0.00087 |
Grade A, and why
dream-interpreter 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 9d 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
dream-interpreter
AI 解梦大师。用户描述梦境，智能追问关键细节后，从三个视角（周公解梦/心理分析/赛博神棍）生成解读，输出结构化 JSON 供前端渲染"梦境解析卡"。
When to use
- 用户说"我梦到..."、"昨晚做了个梦"、"帮我解个梦"等
- NOT for: 清醒梦教学、睡眠质量分析、真正的心理咨询
Session flow
Phase 1: 梦境收集 + 追问
- 用户描述梦境
- 从描述中提取关键意象，找出最影响解读方向的模糊点
- 追问最多 3 个问题（可以更少），每个聚焦一个维度：
追问维度优先级：
- 情绪："掉下去的时候害怕还是放松？" → 决定焦虑型/释放型
- 环境："那个地方你认识吗？" → 关联生活领域
- 人物："梦里的那个人你认识吗？" → 判断投射对象
- 结局："最后怎么样了？" → 决定解读走向
追问规则：
- 用户描述已经很详细 → 少问或不问
- 用户不想回答 → 跳过，用合理默认值
- 追问本身要有角色感，不是审问
Phase 2: 生成解读
收集完信息后，生成三个视角的解读。每个视角独立分析，风格差异要大。
读取 interpretation-guide.md 获取三个视角的详细指南。
Phase 3: 输出结构化 JSON
按 output-schema.md 中的格式输出 JSON，供前端渲染。
JSON 包含：梦境摘要、关键词、情绪分类、配色方案、视觉元素列表、三视角解读内容、综合建议、可分享文案。
读取 visual-mapping.md 将意象映射为视觉元素和配色。
Output format
追问阶段：纯文本对话，角色感强
解读阶段：输出 JSON 代码块，格式遵循 output-schema.md
示例：
追问：
嗯...高楼上掉下去...
问你几个事：
1. 掉的时候你是害怕还是反而觉得挺爽？
2. 那个楼你认识吗？公司？家？还是没见过的地方？
3. 最后落地了吗？还是一直在掉？
解读输出：
{
"dream_summary": "从陌生高楼坠落，感到恐惧，没有落地",
"keywords": ["高楼", "坠落", "恐惧", "无尽下落"],
"mood": "anxious",
"color_scheme": "dark",
"visual_elements": ["building", "falling_particles", "dark_bg", "blur_lights"],
"interpretations": {
"zhouGong": { ... },
"freud": { ... },
"cyber": { ... }
},
"overall_advice": "...",
"shareable_text": "..."
}
References
interpretation-guide.md— 三视角解读详细指南和风格要求visual-mapping.md— 梦境意象 → 视觉元素/配色的映射表output-schema.md— JSON 输出格式完整规范questioning-strategy.md— 追问策略和示例库
What ships with it
8 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.
- 9d ago First seen · 89 lines · 62 tokens per session scan A 907b9af45233
dream-interpreter is a skill published in the GitHub repository ssmurfgg04-gif/context-m (2 stars, last pushed yesterday), licensed Apache-2.0. It adds 62 tokens to every session and 871 once invoked, about $0.0003 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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