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 legendtkl/agentic-skill-router --skill skill-108git clone --depth 1 https://github.com/legendtkl/agentic-skill-routerWrote 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/legendtkl/agentic-skill-router/skill-108)<a href="https://agentmods.dev/skills/legendtkl/agentic-skill-router/skill-108"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-108/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/legendtkl/agentic-skill-router/skill-108"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-108.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 | $0.00019 | $0.00376 |
| Opus 5 | $0.00010 | $0.00188 |
| Sonnet 5 | $0.00004 | $0.00075 |
| Haiku 4.5 | $0.00002 | $0.00038 |
Grade A, and why
skill-108 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 7d 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.
What it actually says
PDF Image Extractor Guide
Overview
This skill allows users to extract images embedded within PDF documents and save them in formats such as JPEG, PNG, or TIFF. This is particularly useful for graphic designers and researchers who require high-quality visuals from PDF sources.
Extraction Process
The process involves reading the PDF file, identifying image objects, and exporting them as standalone image files.
Quick Start
from pypdf import PdfReader
import os
# Function to extract images from a PDF
def extract_images_from_pdf(pdf_file, output_dir):
reader = PdfReader(pdf_file)
if not os.path.exists(output_dir):
os.makedirs(output_dir)
for i, page in enumerate(reader.pages):
images = page.images
for j, img in enumerate(images):
with open(f"{output_dir}/image_{i+1}_{j+1}.png", "wb") as img_file:
img_file.write(img.data)
# Extract images to output directory
extract_images_from_pdf("document.pdf", "extracted_images")
Handling Different Image Formats
Support for saving images in different formats can be added:
from PIL import Image
# Function to save image in different formats
def save_image(image_data, output_path, format='PNG'):
image = Image.open(image_data)
image.save(output_path, format)
# Usage
save_image(image_data, "output_image.jpeg", format='JPEG')
Conclusion
This skill is essential for anyone looking to extract and work with images from PDF documents. For detailed functionality and advanced extraction techniques, refer to docs/pdf_image_extractor.md.
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.
- 7d ago First seen · 52 lines · 19 tokens per session scan A f3977568f0ca
skill-108 is a skill published in the GitHub repository legendtkl/agentic-skill-router (5 stars, last pushed 3mo ago), licensed MIT. It adds 19 tokens to every session and 376 once invoked, about $0.0001 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 2026-09-03.
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