
hermes-history-ingest
Ingest Hermes agent history into Obsidian as distilled knowledge. Use for importing or mining /.hermes sessions, memories, or logs; use wiki-agent for targeted topic-only cross-agent recall.
- Installs
- 2.4K
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/ar9av/obsidian-wiki --skill hermes-history-ingest- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads hermes-history-ingest automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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
Writing profile: Before drafting or rewriting natural-language Markdown, read and apply the Writing Profile Resolution section in llm-wiki/SKILL.md. Framework schema, provenance, safety, and operation-specific requirements take precedence.
WRITING.md preferences apply only to newly drafted or rewritten natural-language Markdown; preserve source content and structured records.
- Resolve config — follow the Config Resolution Protocol in
llm-wiki/SKILL.md(inline@nameoverride → walk up CWD for.env→ global config → prompt setup). This givesOBSIDIAN_VAULT_PATHandHERMES_HISTORY_PATH(defaults to~/.hermes) - Read
.manifest.jsonat the vault root to check what has already been ingested - Read
index.mdat 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_atin 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
memories/*.md/memories/*.json— highest signal; curated persistent knowledge the agent accumulatedsessions/**/*.jsonl— structured turn-by-turn transcripts; rich but noisyconfig.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_resultpairs 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
cwdmetadata 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 confidence and lifecycle fields to every new page:
Leave
base_confidence: 0.42 lifecycle: draft lifecycle_changed: <obsidian-wiki memory now --date>lifecycleunchanged on update. - 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_atsource_type:hermes_memory|hermes_sessionproject: 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, log.md, and hot.md with one locked call:
obsidian-wiki memory sync HERMES_HISTORY_INGEST \
memories=<memories> sessions=<sessions> pages_updated=<pages_updated> \
pages_created=<pages_created> mode=<mode> \
--takeaways "Ingested 42 Hermes memories and 7 sessions; dominant themes: reasoning strategies, tool use patterns."
Never hand-edit index.md, log.md, or hot.md — the command takes the lock that keeps a parallel writer from dropping your update. --takeaways is the one-line conceptual summary that used to go in Recent Activity;
omit it to leave the previous takeaways untouched.
See .skills/llm-wiki/references/MEMORY.md for the full procedure.
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.
QMD Refresh After Vault Writes
QMD is a search index, not the source of truth. If $QMD_WIKI_COLLECTION is empty or unset, skip this step. Run it only after this skill has written or rewritten vault markdown. If QMD refresh fails, do not roll back the vault changes; report the QMD status separately.
Use $QMD_CLI if set; otherwise use qmd.
${QMD_CLI:-qmd} update
If the output says vectors are needed or embeddings may be stale, run:
${QMD_CLI:-qmd} embed
Verify the collection with either:
${QMD_CLI:-qmd} ls "$QMD_WIKI_COLLECTION"
or, when a specific page path is known:
${QMD_CLI:-qmd} get "qmd://$QMD_WIKI_COLLECTION/<page>.md" -l 5
Record one of:
QMD refreshed: update + embed + verifiedQMD refreshed: update only + verifiedQMD skipped: QMD_WIKI_COLLECTION unsetQMD skipped: qmd CLI unavailableQMD failed: <short error summary>
FAQ
What does the hermes-history-ingest skill do?
Ingest Hermes agent history into Obsidian as distilled knowledge. Use for importing or mining /.hermes sessions, memories, or logs; use wiki-agent for targeted topic-only cross-agent recall.
How do I install hermes-history-ingest?
Run npx skills add https://github.com/ar9av/obsidian-wiki --skill hermes-history-ingest in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/hermes-history-ingest/ (personal) or .claude/skills/hermes-history-ingest/ (project).
Which AI agents can use hermes-history-ingest?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is hermes-history-ingest safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains hermes-history-ingest?
It is published by ar9av in ar9av/obsidian-wiki. It has 2,449 recorded installs.
More from ar9av/obsidian-wiki
llm-wiki
ar9av/obsidian-wiki
Explain and apply the foundational LLM Wiki architecture and knowledge-management strategy. Use for setup, architecture, schema, or organization decisions; operational ingest/query/lint work uses dedicated skills.
wiki-ingest
ar9av/obsidian-wiki
Ingest new documents, raw text, folders, or URLs into the Obsidian wiki as distilled, linked knowledge. Use for general wiki ingestion when no more specific ingest skill applies, including processing raw/ staged content.
wiki-setup
ar9av/obsidian-wiki
Initialize or repair an Obsidian wiki vault's required structure and configuration. Use for new-vault setup, .env/config creation, reconfiguration, or broken setup recovery.
wiki-query
ar9av/obsidian-wiki
Search and synthesize answers from the compiled Obsidian wiki, including cited and multi-hop answers. Use for questions about existing wiki knowledge or fast index-only lookups, and for challenge requests ("challenge this", "argue against X", "poke holes in my plan") that look for the vault's own evidence against a plan. Supports named-vault routing such as wiki-query @work; not for ingesting new sources.
wiki-lint
ar9av/obsidian-wiki
Audit wiki health: broken links, orphans, contradictions, stale content, lifecycle and tag issues. Use for maintenance or health checks. Default is report-only; use wiki-dedup for page-identity merges.
wiki-status
ar9av/obsidian-wiki
Report wiki ingestion/completeness state, pending source delta, structural insights, or maintenance equilibrium. Use for remaining-work/status questions, hubs and bridges, or whether maintenance skills still have pending changes. wiki-digest summarizes learned knowledge instead.
Popular productivity & automation skills
agent-browser
vercel-labs/agent-browser
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.
lark-doc
open.feishu.cn
飞书云文档(Docx / Wiki)内容操作:读取、创建、编辑文档,插入或下载图片附件,以及操作思维笔记。用户提供文档 URL/token(包括 doubao.com 的 /docx/、/wiki/)时使用;按 URL 路径/token 而非域名路由;/page/ 是妙搭应用,非飞书云文档。文档内嵌资源按读取参考中的统一规则分流。独立评论操作走 lark-drive;随正文读取评论使用 docs +fetch。表格或 Base 内部数据操作不在本 skill。
lark-base
open.feishu.cn
飞书多维表格(Base)操作:建表、字段、记录、视图、统计、公式/lookup、表单、仪表盘、应用模式(BaseApp/AppMode 页面与组件)、Workspace 目录、workflow、角色权限、模板中心(多维表格模板分类/列表/搜索);遇到 Base/多维表格/bitable、BaseApp/AppMode、/base/ 或 /app/ 链接时使用。BaseApp 不走 lark-apps;文件导入/导出转 lark-drive,认证/授权转 lark-shared。
lark-drive
open.feishu.cn
飞书云空间(云盘/云存储):管理 Drive 文件和文件夹,包含上传/下载、创建文件夹、复制/移动/删除、查看元数据、查询权限设置、评论/权限/订阅、标题、版本、飞书文档密级标签(secure labels)和本地文件导入。用户需要整理云盘目录、处理云空间资源 URL/token、判断链接类型/真实 token/标题,或导入 Word/Markdown/Excel/CSV/PPTX/.base 为 docx/sheet/bitable/slides 时使用;doubao.com 云空间 URL/token 也按资源路径和 token 路由,不回退 WebFetch。不负责:文档内容编辑(走 lark-doc)、表格/Base 表内数据操作(走 lark-sheets/lark-base)、知识空间节点/成员管理(走 lark-wiki)、原生 Markdown 文件读写/patch/diff(走 lark-markdown)。
lark-shared
open.feishu.cn
Use for lark-cli setup/auth tasks: auth login/status/logout, user vs bot identity, business-domain permissions (--domain, including all/docs/drive), missing scopes, revoking authorization, or handling notice JSON.
lark-im
open.feishu.cn
飞书即时通讯:收发消息和管理群聊。发送和回复消息、搜索聊天记录、管理群聊成员、上传下载图片和文件、管理表情回复、发送应用内/短信/电话加急、发送和处理交互卡片(Interactive Card)、监听卡片按钮回调(card.action.trigger)。当用户需要发消息、查看或搜索聊天记录、下载聊天中的文件、查看群成员、搜索群、创建群聊或话题群、管理标记数据、管理 Feed 置顶(添加/移除/查询置顶会话)、管理标签数据、处理卡片回调时使用。