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 feature-flag-policygit 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/feature-flag-policy)<a href="https://agentmods.dev/skills/xberg-io/xberg/feature-flag-policy"><img src="https://agentmods.dev/badge/skills/xberg-io/xberg/feature-flag-policy/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/feature-flag-policy"><img src="https://agentmods.dev/badge/skills/xberg-io/xberg/feature-flag-policy.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 | $0.00093 | $0.02568 |
| Opus 5.5 | $0.00037 | $0.01027 |
| Sonnet 5.5 | $0.00019 | $0.00514 |
| Haiku 4.5 | $0.00009 | $0.00257 |
Grade A, and why
feature-flag-policy 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 13d 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Flag Policy
All features in crates/xberg/Cargo.toml.
ORT-Incompatible Targets (WASM, Android x86_64 emulator)
Only ORT-dependent paths are incompatible. The same paths block both WASM (no native ORT linkage at all) and the x86_64-linux-android emulator triple (no pyke prebuilt; aarch64-linux-android does ship a prebuilt and gets full ORT):
paddle-ocr— ONNX Runtime + native C++ deps: not WASM-safe; no Android x86_64 prebuiltlayout-detection— depends on ONNX Runtime layout models: not WASM-safe; no Android x86_64 prebuilt (RT-DETR + table classifier are available off-ORT via thelayout-tractsibling, below)embeddings— depends on ONNX Runtime sentence-transformer models: not WASM-safe; no Android x86_64 prebuiltauto-rotate— depends on ONNX Runtime orientation classifier: not WASM-safe; no Android x86_64 prebuilt (available off-ORT via theauto-rotate-tractsibling, below)formula-recognition— LaTeX recognition for layout formula regions (RapidLaTeXOCR ONNX): ORT-dependent, opt-in, excluded fromfull/formats
Pure-Rust type-only companion features expose the public config/result types for the above without pulling in ORT:
layout-types—LayoutDetectionConfig,TableModel,BBox,DetectionResult,LayoutClass,LayoutDetection,RecognizedTable.layout-detectionimplieslayout-types.auto-rotate-types—OrientationResult.auto-rotateimpliesauto-rotate-types.embedding-presets—EmbeddingPreset(already existed; pure-Rust preset metadata).
Pure-Rust tract inference variants run select ONNX models where native ORT cannot link, loading the
same .onnx artifacts through the tract engine (CPU-only, no native library):
layout-detection(ORT) →layout-tract(tract): RT-DETR layout detection + the PP-LCNet wired/wireless table classifier run on WASM and the Android x86_64 emulator. TATR, SLANeXT, PP-DocLayout-V3, and YOLO stay ONNX Runtime-only (tract 0.23.4 op-coverage gaps).auto-rotate(ORT) →auto-rotate-tract(tract): PP-LCNet document-orientation on WASM and the Android x86_64 emulator.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 13d ago Changed · +6 lines · -5 tokens per session a000ca5db25d
- 23d ago Changed · -1 lines 5e7615edbef6
- 1mo ago First seen · 117 lines · 98 tokens per session scan A 5d63586c71f8
feature-flag-policy is a skill published in the GitHub repository xberg-io/xberg (9,444 stars, last pushed today), licensed MIT. It adds 93 tokens to every session and 2,568 once invoked, about $0.0004 per session on Opus 5.5. 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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