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Agent Skill · 前端设计

hermes-history-ingest(爱马仕历史摄取)

hermes-history-ingest 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

hermes-history-ingest 是前端设计类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在前端设计类的 10,216 个 Skill 里排第 864。

总安装 10,536周安装 439GitHub Stars 801下载 3,512核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:hermes-history-ingest(爱马仕历史摄取)
来源仓库:https://github.com/ar9av/obsidian-wiki
仓库路径:skills/hermes-history-ingest
安装命令:
npx skills add https://github.com/ar9av/obsidian-wiki --skill hermes-history-ingest
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/ar9av/obsidian-wiki --skill hermes-history-ingest

这个 Skill 是做什么的

前端设计类 Skill 关注页面结构、视觉规范和组件写法,输出通常是可运行的界面代码。

hermes-history-ingest 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理。

通过 npx skills add 命令从指定 GitHub 仓库安装,需确认权限和维护状态。使用前建议核验具体用法,注意是否会触发联网、命令执行或文件读写操作。涉及敏感数据时应先确认脱敏边界和操作权限,避免误改生产环境。

来源仓库内路径:skills/hermes-history-ingest

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/ar9av/obsidian-wiki --skill hermes-history-ing…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

hermes-history-ingest 怎么安装?

在终端执行 npx skills add https://github.com/ar9av/obsidian-wiki --skill hermes-history-ingest。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

hermes-history-ingest 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

hermes-history-ingest 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

hermes-history-ingest 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

hermes-history-ingest 用的人多吗?

公开数据是累计安装 10,536 次,近一周安装 439 次,下载 3,512 次,GitHub 801 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

hermes-history-ingest 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理前端设计类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

前端设计类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
frontend-design

前端设计 · Codex、Claude

8,823,360126,072只读MIT通过
vercel-composition-patterns

Vercel 组合模式 · Codex、Claude

3,858,81625,893需要联网MIT通过
vercel-react-native-skills

Vercel React native skills 前端 · Codex、Claude

2,468,66425,878只读MIT通过
adapt

adapt 搜索 · Codex、Claude

2,027,04023,125操作浏览器未明确通过
bolder

bolder 分析 · Codex、Claude

2,004,28823,130只读未明确通过
hermes-history-ingest

爱马仕历史摄取 · 本页

10,536801需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Hermes History Ingest — Conversation & Memory Mining

You are extracting knowledge from the user's Hermes agent history and distilling it into the Obsidian wiki. Hermes stores both free-form memories and structured session transcripts — focus on durable knowledge, not operational telemetry.

This skill can be invoked directly or via the wiki-history-ingest router (/wiki-history-ingest hermes).

Before You Start

  1. Read .env to get OBSIDIAN_VAULT_PATH and HERMES_HISTORY_PATH (default to ~/.hermes if unset)
  2. Read .manifest.json at the vault root to check what has already been ingested
  3. Read index.md at the vault root to understand what the wiki already contains

Ingest Modes

Append Mode (default)

Check .manifest.json for each source file. Only process:

  • Files not in the manifest (new memory files, new session logs)
  • Files whose modification time is newer than ingested_at in the manifest

Use this mode for regular syncs.

Full Mode

Process everything regardless of manifest. Use after wiki-rebuild or if the user explicitly asks for a full re-ingest.

Hermes Data Layout

Hermes stores all local artifacts under ~/.hermes/ (or $HERMES_HOME for non-default profiles).

~/.hermes/
├── memories/                          # Persistent agent memories (markdown or JSON)
│   └── *.md / *.json
├── skills/                            # Installed skills (read-only for ingest purposes)
│   └── <skill-name>/SKILL.md
├── sessions/                          # Session transcripts (if session logging is enabled)
│   └── YYYY-MM-DD/
│       └── <session-id>.jsonl
├── config.yaml                        # User config (model, theme, paths)
└── .hub/                              # Skills Hub state (lock.json, audit.log, quarantine/)

Key data sources ranked by value

  1. memories/*.md / memories/*.json — highest signal; curated persistent knowledge the agent accumulated
  2. sessions/**/*.jsonl — structured turn-by-turn transcripts; rich but noisy
  3. config.yaml — metadata only (model preferences, paths); rarely worth ingesting

Skip .hub/ internals (audit/quarantine state) and the skills/ directory (source material, not user knowledge).

Step 1: Survey and Compute Delta

Scan HERMES_HISTORY_PATH and compare against .manifest.json:

  • ~/.hermes/memories/
  • ~/.hermes/sessions/**/ (if present)

Classify each file:

  • New — not in manifest
  • Modified — in manifest but file is newer than ingested_at
  • Unchanged — already ingested and unchanged

Report a concise delta summary before deep parsing.

Step 2: Parse Memories First

Memories are the highest-value source. Hermes writes them as either:

  • Markdown — structured prose with optional frontmatter; ingest directly
  • JSON — {"content": "...", "created_at": "...", "tags": [...]} records

For each memory:

  • Extract the core knowledge claim
  • Note any tags Hermes attached (they often map to wiki categories)
  • Merge into the appropriate wiki page rather than creating one memory = one page

Step 3: Parse Session JSONL Safely

Each session JSONL line is an event envelope. Common shapes:

{"role": "user", "content": "..."}
{"role": "assistant", "content": "..."}
{"type": "tool_use", "name": "...", "input": {...}}
{"type": "tool_result", "content": "..."}

Extraction rules

  • Prioritize assistant responses that state conclusions, patterns, or decisions
  • Extract user intent from high-signal turns; skip low-information follow-ups
  • Treat tool_use / tool_result pairs as context, not primary content
  • Skip token accounting, internal plumbing, and repeated plan echoes

Critical privacy filter

Session logs can include injected instructions, tool payloads, and sensitive text. Do not ingest verbatim.

  • Remove API keys, tokens, passwords, credentials
  • Redact private identifiers unless relevant and user-approved
  • Summarize; do not quote raw transcripts verbatim

Step 4: Cluster by Topic

Do not create one wiki page per memory or session.

  • Group memories by stable topic (concept, tool, project, technique)
  • Split mixed sessions into separate themes
  • Merge recurring patterns across dates and projects
  • Use file paths or session cwd metadata to infer project scope when available

Step 5: Distill into Wiki Pages

Route extracted knowledge using existing wiki conventions:

  • Project-specific architecture/process → projects/<name>/...
  • General concepts → concepts/
  • Recurring techniques/debug playbooks → skills/
  • Tools/services/frameworks → entities/
  • Cross-session patterns → synthesis/

For each impacted project, create/update projects/<name>/<name>.md.

Writing rules

  • Distill knowledge, not chronology
  • Avoid "on date X we discussed..." unless date context is essential
  • Add summary: frontmatter on each new/updated page (1–2 sentences, ≤ 200 chars)
  • Add provenance markers:

- ^[extracted] when directly grounded in explicit memory/session content - ^[inferred] when synthesizing patterns across multiple memories - ^[ambiguous] when memories conflict

  • Add/update provenance: frontmatter mix for each changed page

Step 6: Update Manifest, Log, and Index

Update .manifest.json

For each processed source file:

  • ingested_at, size_bytes, modified_at
  • source_type: hermes_memory | hermes_session
  • project: inferred project name (when applicable)
  • pages_created, pages_updated

Add/update a top-level summary block:

{
  "hermes": {
    "source_path": "~/.hermes/",
    "last_ingested": "TIMESTAMP",
    "memories_ingested": 42,
    "sessions_ingested": 7,
    "pages_created": 5,
    "pages_updated": 12
  }
}

Update special files

Update index.md and log.md:

- [TIMESTAMP] HERMES_HISTORY_INGEST memories=N sessions=M pages_updated=X pages_created=Y mode=append|full

hot.md — Read $OBSIDIAN_VAULT_PATH/hot.md (create from the template in wiki-ingest if missing). Update Recent Activity with a one-line summary — e.g. "Ingested 42 Hermes memories and 7 sessions; dominant themes: reasoning strategies, tool use patterns." Keep the last 3 operations. Update updated timestamp.

Privacy and Compliance

  • Distill and synthesize; avoid raw memory or transcript dumps
  • Default to redaction for anything that looks sensitive
  • Ask the user before storing personal or sensitive details
  • Keep references to other people minimal and purpose-bound

Reference

See references/hermes-data-format.md for field-level notes and extraction guidance.

平台分布

Codex

34.48%
按下载量换算1,211

Claude

31.15%
按下载量换算1,094

Cursor

17.51%
按下载量换算615

Gemini CLI

9.15%
按下载量换算321

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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