personal-knowledge-ingestion

personal-knowledge-ingestion is a skill for Claude Code, Codex from lyc403223157-source/knowledge-inbox. It costs 86 tokens per session (534 once invoked), scanned A, original, Apache-2.0.

A skill for saving links, videos, social posts, local files, screenshots, PDFs, or text into an Obsidian vault, a folder used for personal notes and knowledge. It uses connected knowledge tools to process and format the saved item.

In plain words
What is it for?
Archiving supplied content, including WeChat Channels videos and X posts, and saving summaries or source material to Obsidian.
Why use it?
It keeps useful information in one searchable knowledge base instead of leaving it scattered across websites, files, and messages.

Skill for Claude CodeCodex

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

Good fit Archiving supplied content, including WeChat Channels videos and X posts, and saving summaries or source material to Obsidian.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/lyc403223157-source/knowledge-inbox/personal-knowledge-ingestion
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 lyc403223157-source/knowledge-inbox --skill personal-knowledge-ingestion
Clone the repo
git clone --depth 1 https://github.com/lyc403223157-source/knowledge-inbox

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 personal-knowledge-ingestion

README.md
[![agentmods](https://agentmods.dev/badge/skills/lyc403223157-source/knowledge-inbox/personal-knowledge-ingestion/github.svg)](https://agentmods.dev/skills/lyc403223157-source/knowledge-inbox/personal-knowledge-ingestion)
Your own site
<a href="https://agentmods.dev/skills/lyc403223157-source/knowledge-inbox/personal-knowledge-ingestion"><img src="https://agentmods.dev/badge/skills/lyc403223157-source/knowledge-inbox/personal-knowledge-ingestion/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 personal-knowledge-ingestion

Your own site · 80×15
<a href="https://agentmods.dev/skills/lyc403223157-source/knowledge-inbox/personal-knowledge-ingestion"><img src="https://agentmods.dev/badge/skills/lyc403223157-source/knowledge-inbox/personal-knowledge-ingestion.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 534 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 $0.00086 $0.00534
Opus 5 $0.00043 $0.00267
Sonnet 5 $0.00017 $0.00107
Haiku 4.5 $0.00009 $0.00053

Measured 9d ago against content hash 40aac223b63a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

personal-knowledge-ingestion 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.

hermes-skill/personal-knowledge-ingestion/SKILL.md · 44 lines

How it starts

The opening of the file, as written. The whole thing — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Personal Knowledge Ingestion

Use the knowledge_ingest tool when the user explicitly asks to save, ingest, archive, or add supplied content to their personal knowledge base.

Tool input

  • content: pass the exact URL, absolute local file path, or original text.
  • title: optional user-provided title. Do not invent one unless it improves a text-only note.
  • source_url: only use when content is a local file that came from a known web URL.
  • timeout_seconds: normally omit; use up to 1800 for long media.

Behavior

  • Call the tool once and wait for its result.
  • Do not separately summarize the content; the ingestion pipeline performs AI understanding, classification, tags, linking, and Markdown formatting.
  • On success, report the returned absolute note_path.
  • On failure, report the exact actionable error and never claim the note was saved.
  • For WeChat Channels links, the tool starts the local downloader, temporarily enables the approved SunnyNet proxy, and uses one logged-in Channels page as a local API client. It must not ask the user to open the supplied video URL. Never call scripts/ingest.py directly for these links. If knowledge_ingest reports that the client is disconnected, call knowledge_wechat_prepare immediately and retry knowledge_ingest after it returns ready. Do not investigate the downloader with terminal or browser tools, and do not invent alternative workflows. If preparation reports that the Hermes Python binary lacks Accessibility permission, return that exact binary path and the single required permission action. For any other preparation failure, ask the user once to close and reopen any Channels window; never ask them to open or play the supplied video. This bootstrap is needed only after WeChat or its renderer restarts. The tool always restores the system proxy to off and deletes the downloaded video only after the card and database write succeed.
  • Do not call this tool for read-only questions about existing notes.

Read the full file on GitHub · 44 lines

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. 9d ago First seen · 44 lines · 86 tokens per session scan A 40aac223b63a

Subscribe to this mod's changes

personal-knowledge-ingestion is a skill published in the GitHub repository lyc403223157-source/knowledge-inbox (7 stars, last pushed 4d ago), licensed Apache-2.0. It adds 86 tokens to every session and 534 once invoked, about $0.0004 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 2026-08-31.

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