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 nrl-ai/chub --skill document-workflowsgit clone --depth 1 https://github.com/nrl-ai/chubWrote 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/nrl-ai/chub/document-workflows)<a href="https://agentmods.dev/skills/nrl-ai/chub/document-workflows"><img src="https://agentmods.dev/badge/skills/nrl-ai/chub/document-workflows/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/nrl-ai/chub/document-workflows"><img src="https://agentmods.dev/badge/skills/nrl-ai/chub/document-workflows.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00259 | $0.07988 |
| Opus 5.5 | $0.00104 | $0.03195 |
| Sonnet 5.5 | $0.00052 | $0.01598 |
| Haiku 4.5 | $0.00026 | $0.00799 |
Grade A, and why
document-workflows 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 1mo 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.
This is a copy
100% identical to document-workflows — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 864 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Document Workflows — ADE Pipeline Patterns
Overview
This skill provides reusable building blocks for composing LandingAI ADE
primitives (parse, extract, split) into production-ready document processing
pipelines. It complements the document-extraction skill:
| Concern | document-extraction |
document-workflows |
|---|---|---|
| Scope | ADE SDK API: parse, extract, split, grounding | End-to-end pipelines: batch, RAG, DB, classify-route |
| When | Need to call a single ADE operation | Need to compose operations into a workflow |
| Code | SDK method calls with parameters | Complete functions with error handling, parallelism |
| Deps | landingai-ade only |
+ workflow-specific libs (pandas, chromadb, etc.) |
Philosophy: Organize by workflow pattern (batch, RAG, DB insertion), not by document type. The same pattern applies whether documents are invoices, utility bills, or medical forms.
Step 0 (mandatory) — Pre-Flight Document Exploration {#pre-flight}
Run this before writing any pipeline code whenever working with documents whose internal structure has not already been inspected in this session.
Rule: never write section-detection, heading-matching, or text-search code without first running Tool 2 (diagnostic parse) on the sample document. Heading format is document-specific and cannot be inferred from the task description or document type alone — the only reliable way to know it is to look at the actual ADE output.
Common surprises: a paper's "Introduction" heading may appear as
1. Introduction(plain text, no#),## Introduction,INTRODUCTION(all-caps), or embedded inside a text chunk with body copy. Getting this wrong means a silent failure (zero chunks matched) that requires a full re-parse to debug.
Run Tool 1 (visual render) and Tool 2 (diagnostic parse) on 1–3 representative sample documents before writing any code. This takes under a minute and prevents debugging iterations that a pre-flight would have avoided.
What ships with it
6 files 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.
- 1mo ago First seen · 864 lines · 259 tokens per session scan A 64f7e9058cfd
document-workflows is a skill published in the GitHub repository nrl-ai/chub (11 stars, last pushed 6mo ago), licensed MIT. It adds 259 tokens to every session and 7,988 once invoked, about $0.0010 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to document-workflows, differing in 0 lines, and is treated as a copy.
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