Context Hub is a repository and command-line tool that supplies coding agents with curated, versioned documentation and skills in markdown form. It is for agents that need accurate API information across tasks, and the catalogue entries provide skills for searching, fetching, and improving that context.
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 andrewyng/context-hub --skill document-extractiongit clone --depth 1 https://github.com/andrewyng/context-hubWrote 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/andrewyng/context-hub/document-extraction)<a href="https://agentmods.dev/skills/andrewyng/context-hub/document-extraction"><img src="https://agentmods.dev/badge/skills/andrewyng/context-hub/document-extraction/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/andrewyng/context-hub/document-extraction"><img src="https://agentmods.dev/badge/skills/andrewyng/context-hub/document-extraction.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 7 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 50 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 70 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 79 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 95 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 58 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 59 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 60 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00222 | $0.08441 |
| Opus 5.5 | $0.00089 | $0.03376 |
| Sonnet 5.5 | $0.00044 | $0.01688 |
| Haiku 4.5 | $0.00022 | $0.00844 |
Grade A, and why
document-extraction 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- document-extraction — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 994 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Document Extraction (ADE)
Overview
LandingAI's Agentic Document Extraction (ADE) is a document processing SaaS that parses, extracts, and classifies documents without requiring templates or training. It provides three main capabilities:
- Parse: Convert documents into structured Markdown with hierarchical JSON representation
- Extract: Pull specific structured data using JSON schemas or Pydantic models
- Split: Classify and separate multi-document batches by type
Key Benefits:
- No ML training or templates required
- Layout-agnostic parsing (works with any document structure)
- Supports 20+ file formats (PDF, images, spreadsheets, presentations)
- Precise visual grounding (bounding boxes, page numbers)
- Multiple models optimized for different document types
Quick Start
1. Installation
Never install packages globally without user approval. Always check for a local Python environment first.
1. .venv/bin/python — uv-managed (this project)
2. venv/bin/python — standard Python venv
3. uv run python — if pyproject.toml exists
4. poetry run python — if poetry.lock exists
5. python3 — system fallback; warn the user
Use the local environment to install: landingai-ade, python-dotenv
2. API Key Setup
The user may have already setup a .env file in the same directory as the document-extraction skill with the API key. You MUST check this path first (ls -la .*/skills/document-extraction/.env). Also try checking on the same directory as this SKILL.md file.
If not, provide instructions to create one. The script below will search for .env in common locations and load it.
.venv/bin/python - << 'EOF'
import os
from pathlib import Path
from dotenv import load_dotenv
# Load API key: prefer existing env var, then .env file lookup
if os.environ.get("VISION_AGENT_API_KEY"):
print("API key found in existing environment variable")
else:
def _find_env():
for d in [Path.cwd().resolve(), *Path.cwd().resolve().parents]:
for candidate in [
# ADD the directory where the document-extraction skill is located
d / '.env',
d / 'document-extraction/.env',
d / 'skills/document-extraction/.env',
]:
if candidate.is_file():
return candidate
return None
env = _find_env()
if env:
load_dotenv(env)
print(f"API key loaded from: {env}")
else:
print("Warning: VISION_AGENT_API_KEY not set and no .env found")
EOF
What ships with it
7 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 · 994 lines · 222 tokens per session scan A ff91d6eac78f
document-extraction is a skill published in the GitHub repository andrewyng/context-hub (13,972 stars, last pushed 4mo ago), licensed MIT. It adds 222 tokens to every session and 8,441 once invoked, about $0.0009 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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