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-054git 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-054)<a href="https://agentmods.dev/skills/legendtkl/agentic-skill-router/skill-054"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-054.svg" alt="Measured on agentmods" 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 | $0.00030 | $0.00519 |
| Opus 5 | $0.00015 | $0.00260 |
| Sonnet 5 | $0.00006 | $0.00104 |
| Haiku 4.5 | $0.00003 | $0.00052 |
Grade A, and why
skill-054 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
PPTX Image Management
Overview
Managing images in PowerPoint presentations can enhance the visual appeal and overall effectiveness of your slides. This skill provides methods to insert, format, and optimize images within .pptx files.
Inserting Images
Basic Insertion
You can insert images into your PowerPoint slides using the following method:
from pptx import Presentation
from pptx.util import Inches
# Load the presentation
prs = Presentation('path-to-file.pptx')
# Adding a new slide
slide_layout = prs.slide_layouts[5] # Using a blank layout
slide = prs.slides.add_slide(slide_layout)
# Specify the image file
img_path = 'path-to-image.jpg'
# Insert image
left = Inches(1)
top = Inches(1)
slide.shapes.add_picture(img_path, left, top)
# Save the presentation
prs.save('updated-presentation.pptx')
Advanced Insertion with Formatting
To maintain uniformity, you may want to format images after insertion:
from pptx.dml.color import RGBColor
# Set formatting options
picture = slide.shapes[-1] # Get the last inserted picture
picture.width = Inches(5)
picture.height = Inches(3)
# Set the border
border = picture.line
border.color.rgb = RGBColor(255, 255, 255) # White border
border.width = Inches(0.05)
Optimizing Images
Images can take up a significant amount of space in a presentation. It's often beneficial to compress images to reduce the overall file size:
Compressing Images
You can utilize the following method to compress images within a PowerPoint presentation:
def compress_images(prs):
for slide in prs.slides:
for shape in slide.shapes:
if shape.shape_type == 13: # Check if the shape is a picture
shape.image.compress(quality=50)
# Load the presentation
prs = Presentation('path-to-file.pptx')
compress_images(prs)
prs.save('compressed-presentation.pptx')
Conclusion
Image management is essential for creating effective PowerPoint presentations. By inserting and optimizing images, you can enhance user engagement and presentation clarity.
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 · 76 lines · 30 tokens per session scan A 3fbc126e98db
skill-054 is a skill published in the GitHub repository legendtkl/agentic-skill-router (5 stars, last pushed 3mo ago), licensed MIT. It adds 30 tokens to every session and 519 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 2026-08-31.
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