Ingest

Use this skill to bring external web content into the LLM context window without copy-pasting raw HTML or burning tokens on uncompressed prose:

• Web content → cloud load / cloud search → returns HQCC (a compressed, LLM-optimized form). Cache hits are free.

Local documents (PDF text extraction + OCR) are handled by the liteparse skill, not here — it's a local-first, zero-network tool with Tesseract + PDFium bundled. ingest covers web URLs only.

If your runtime registers the workspace_web_search / web_load tools (Hermes agents do), prefer them over the CLI — same workspace-billed cloud lane (/api/context/load). Never script HTTP via execute_code/subprocess for web research.

When to use

• The user pastes a URL or asks "what does this page say".
• The user asks to research a topic ("AI agent frameworks 2025") — use search to fetch top-K relevant pages.
• A task description contains URLs that need to be resolved into actual content before the assignee can act.

Attached PDFs / images / scans → use the liteparse skill (local-first PDF text + OCR), not ingest.

CLI Reference

# Single URL → HQCC
cloud load https://example.com
cloud load https://example.com --format raw     # exact wording / code / tables (more tokens)

# Batch (up to 50 URLs)
cloud load https://a.com https://b.com https://c.com

# Search → load (fetch top-K relevant pages)
cloud search "AI agent frameworks 2025"
cloud search "topic" -k 10

# Pre-save to cache (e.g. content you scraped elsewhere)
cloud context save https://example.com "compressed content"

Workflow

For web URLs

1. Decide: single URL load? Batch? Or search query?
2. Default to --format hqcc (compressed). Use raw only when exact wording, code, or tables are needed.
3. Run cloud load / cloud search and capture: source URLs, titles, cache status, cost.
4. Base downstream reasoning only on the returned content. If a load failed, say so; don't pretend you read it.

Operating Rules

Load / Search

• Prefer cached context. Don't re-process the same source — the service handles cache lookup automatically; just don't re-issue identical loads in tight loops.
• Preserve source URLs in your notes and citations. The HQCC return retains origin pointers; use them.
• Don't claim to have read a source until the load succeeds. If it fails (404, blocked, timeout), report the failed URL and continue only with clearly stated assumptions or ask for a better source.
• --format raw costs more tokens. Only use when the user needs exact wording (legal text, code snippets, tables that compress badly).
• For batch loads, the service runs them concurrently up to a limit; you don't need to throttle yourself.
• For a document / image / scan (not a web page), hand off to the liteparse skill — ingest does not do OCR or PDF extraction.

Output reporting

After load/search:

• One-line summary per source: <title> · <url> · cache_hit | fresh · <cost>
• Then proceed with the user's actual question, citing the source by URL.

Backing capabilities (D22 mapping)

Replaces the v1.x built-in skill context-load. Local document OCR / extraction (formerly parse-document, backed by the now-retired parser.prismer.dev service) moved to the local-first liteparse skill.