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-055git 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-055)<a href="https://agentmods.dev/skills/legendtkl/agentic-skill-router/skill-055"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-055.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 | $0.00027 | $0.00426 |
| Opus 5 | $0.00014 | $0.00213 |
| Sonnet 5 | $0.00005 | $0.00085 |
| Haiku 4.5 | $0.00003 | $0.00043 |
Grade A, and why
skill-055 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
Scene Renderer Skill
This skill provides a scene_renderer module to create, manipulate, and display game scenes in real-time.
When to use
- Game Development: To visualize environments during development.
- Level Editors: For building and testing levels in a game.
- Showcasing: To create demos or trailers for a game.
How to use
Import the module:
from scene_renderer import Scene, Entity, Camera
1. The Scene Class
The primary container for all entities and the camera.
scene = Scene()
2. Adding Entities
Define and add objects to the scene.
entity = Entity(id="tree", model="tree_model.obj", position=(10, 0, 20))
scene.add_entity(entity)
3. Setting Up the Camera
Define the camera parameters.
camera = Camera(position=(0, 5, -10), look_at=(0, 0, 0))
scene.set_camera(camera)
4. Rendering the Scene
Render the current scene to the display.
scene.render() # Renders the current frame to the screen
5. Updating Entities
Update the state of entities every frame.
for entity in scene.entities:
entity.update() # Move, rotate, or animate entities
6. Saving Scene State
Serialize the current scene to JSON format.
scene_data = scene.to_json() # Save the scene state
7. Loading a Scene
Load an existing scene from JSON.
scene.from_json(scene_data) # Load the scene state from JSON
This skill aims to streamline the process of rendering game scenes, enabling developers to create visually appealing environments quickly.
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 · 68 lines · 27 tokens per session scan A 21be4c314a6e
skill-055 is a skill published in the GitHub repository legendtkl/agentic-skill-router (5 stars, last pushed 3mo ago), licensed MIT. It adds 27 tokens to every session and 426 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 2026-08-31.
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