Xberg is a document-intelligence engine that reads files, URLs, archives, and source trees and extracts text, metadata, images, tables, and structured data, with additional code-language understanding. Developers use it through language bindings, a command-line tool, REST API, or MCP server, and the catalogue entries support those integrations.
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.
npx skills add xberg-io/xberg --skill extraction-pipeline-patternsgit clone --depth 1 https://github.com/xberg-io/xbergWrote 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.
[](https://agentmods.dev/skills/xberg-io/xberg/extraction-pipeline-patterns)<a href="https://agentmods.dev/skills/xberg-io/xberg/extraction-pipeline-patterns"><img src="https://agentmods.dev/badge/skills/xberg-io/xberg/extraction-pipeline-patterns/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.
<a href="https://agentmods.dev/skills/xberg-io/xberg/extraction-pipeline-patterns"><img src="https://agentmods.dev/badge/skills/xberg-io/xberg/extraction-pipeline-patterns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00049 | $0.01771 |
| Opus 5 | $0.00024 | $0.00886 |
| Sonnet 5 | $0.00010 | $0.00354 |
| Haiku 4.5 | $0.00005 | $0.00177 |
Grade A, and why
extraction-pipeline-patterns 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.
How it starts
The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Extraction Pipeline Patterns
Format detection → extractor routing → post-processing, across 106 formats / 140 file extensions
The full-registry counts are verified against published claims by
scripts/sync_supported_counts.py verify. Runtime SUPPORTED_FORMAT_COUNT and
SUPPORTED_EXTENSION_COUNT values are derived from the full static FORMATS registry.
Layout
crates/xberg/src/core/pipeline/— orchestration (mod.rs,cache.rs,execution.rs,features.rs,format.rs,initialization.rs,page_markers.rs)crates/xberg/src/core/mime.rs,core/formats.rs— detection and theFORMATSregistrycrates/xberg/src/extractors/— one module per format, each implementingInternalDocumentExtractorcrates/xberg/src/extraction/— shared parsing/rendering helpers used by those extractorscrates/xberg/src/core/config/,core/config_validation/— both directories, not files
Flow
- Detect — MIME from extension via
EXT_TO_MIME, or from bytes viadetect_mime_type_from_bytes; validate againstSUPPORTED_MIME_TYPES. - Route — registry returns the highest-
priority()extractor registered for that MIME. - Extract — the extractor produces an
InternalDocument. - Post-process —
core::pipeline::run_pipeline(doc, config)(async) orrun_pipeline_sync(WASM) runs validators, quality processing, chunking and hooks, and returnsExtractedDocument. Every extraction path goes through it.
Extractor modules
- Office: DOCX, PPTX, PPT, DOC, XLSX/XLS, ODT, ODP, iWork, HWP/HWPX, and WordPerfect under
extractors/{docx,pptx,ppt,doc,excel,odt,odp,hwp,hwpx,wordperfect}.rsandextractors/iwork/. - Markup: Markdown, text, RST, Org, RTF, AsciiDoc, Typst, and Djot under
extractors/{markdown,text,rst,orgmode,asciidoc,typst}.rsandextractors/{rtf,djot_format}/. - Academic: LaTeX, BibTeX, JATS, Jupyter, DocBook, EPUB, and FictionBook under
extractors/{bibtex,jupyter,docbook,fictionbook}.rsandextractors/{latex,jats,epub}/. - PDF: text, encrypted-document, and OCR-fallback handling under
extractors/pdf/. - Images: PNG, JPEG, TIFF, WebP, HEIC, SVG, and QR under
extractors/andextraction/. - Web: HTML, XHTML, XML, and MDX under
extractors/andextraction/html/. - Email: EML, MSG, and PST under
extractors/andextraction/email.rs. - Archives: ZIP, TAR, GZIP, and 7z under
extractors/archive.rsandextraction/archive/. - Structured: JSON, GeoJSON, YAML, TOML, CSV, DBF, SQLite, and GeoPackage under
extractors/.
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.
- 9d ago First seen · 127 lines · 49 tokens per session scan A fb76fafa8636
extraction-pipeline-patterns is a skill published in the GitHub repository xberg-io/xberg (9,275 stars, last pushed yesterday), licensed MIT. It adds 49 tokens to every session and 1,771 once invoked, about $0.0002 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 2026-08-30.
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