# Knowledge Ingest > Ingest URLs, documents, and text into the memory system as structured knowledge Use when this capability is needed. - Skill: `tomevault-io/knowledge-ingest` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/knowledge-ingest` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/knowledge-ingest/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/knowledge-ingest --- # Knowledge Base Ingestion Transform external content -- web pages, documents, raw text -- into structured semantic memories that persist in the knowledge graph. ## When to Use - When the user shares a URL and says "learn this" or "remember this article" - When a research workflow finds valuable sources that should be retained long-term - When the user pastes raw text (notes, transcripts, outlines) to be ingested - During heartbeats when a goal involves building knowledge on a specific topic - When importing reference material for a project or domain ## Step-by-Step Methodology 1. **Assess the source**: Before ingesting, determine what kind of content it is (article, documentation, transcript, raw notes). This guides how aggressively to summarize. 2. **Fetch and parse**: For URLs, use `ingest_url` which handles fetching, HTML-to-text conversion, and chunking. For raw text, use `ingest_text` directly. 3. **Check for duplicates**: Use `recall` with the URL or a key phrase from the content to see if it has already been ingested. Avoid storing the same source twice. 4. **Chunk intelligently**: Long content is automatically chunked by the ingestion pipeline. Each chunk becomes a separate semantic memory linked by source metadata. Trust the pipeline's chunking; do not manually split content unless it is clearly failing. 5. **Add context**: When storing via `remember`, include metadata about the source: URL, author, date published, and why it was ingested (which goal or topic it serves). 6. **Verify ingestion**: After ingestion completes, run a quick `recall` on a key concept from the content to confirm it is retrievable. 7. **Connect to goals**: If the ingested content relates to an active goal, note the connection so future heartbeats can leverage it. ## Quality Guidelines - Prefer ingesting authoritative, primary sources over summaries or aggregators. - Do not ingest entire websites. Be selective -- ingest the specific pages that contain the needed information. - When ingesting long documents, let the chunking pipeline do its job. Each chunk retains a reference to the parent source. - Always record the source URL or origin. Memories without provenance are harder to evaluate and update later. - Respect rate limits and robots.txt when fetching URLs. If a fetch fails, note the failure and move on rather than retrying aggressively. - For sensitive or private content (internal docs, personal notes), ensure the user understands that ingested content persists in the local database. --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/quixiai) — claim your Tome and manage your conversions.