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-107git 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-107)<a href="https://agentmods.dev/skills/legendtkl/agentic-skill-router/skill-107"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-107/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-107"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-107.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 | $0.00028 | $0.00608 |
| Opus 5 | $0.00014 | $0.00304 |
| Sonnet 5 | $0.00006 | $0.00122 |
| Haiku 4.5 | $0.00003 | $0.00061 |
Grade A, and why
skill-107 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.
How it starts
The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
D3.js Network Visualization Skill
Use this skill to create visual representations of network structures such as social networks, data relationships, or any interconnected systems using D3.js. The goal is to provide users with a visual insight into how different nodes are connected.
When to use
Activate this skill when the user asks for any of the following:
- "Visualize a network of relationships"
- "Create a social network graph"
- "Show connections between entities"
- "Map out a data relationship structure"
If the user requires more traditional data visualizations (e.g., charts, graphs), don’t use this skill—opt for the D3.js Visualization Skill instead.
Inputs you should expect
- One or more local data files:
*.jsonor*.csvcontaining node and link data - A network intent:
- Node attributes (e.g., id, name, group)
- Link attributes (e.g., source, target, relationship type)
- Visualization preferences (e.g., layout type, force-directed graph)
- Output constraints:
- Interactivity level (e.g., "hover to display details" or "click to expand nodes")
If details are missing, make reasonable defaults and document them in comments near the top of the output file.
Outputs you should produce
Prefer producing all of the following when feasible:
dist/network.html— standalone HTML that renders the network visualizationdist/network.svg— exported SVG representation of the network- (Optional)
dist/network.json— if the task requires a data export of the network structure
Always keep outputs in a predictable folder (default: dist/), unless the task specifies paths.
Network visualization principles (non-negotiable)
To create effective network visualizations:
Layout considerations
- Use a force-directed layout for dynamic representations unless specified otherwise.
- Provide options for different layouts (e.g., radial, hierarchical) based on user needs.
Interactivity features
- Implement tooltips for nodes and links to display additional information on hover.
- Allow users to zoom and pan to explore dense network areas efficiently.
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 · 80 lines · 28 tokens per session scan A 6b0a3e6418dc
skill-107 is a skill published in the GitHub repository legendtkl/agentic-skill-router (5 stars, last pushed 3mo ago), licensed MIT. It adds 28 tokens to every session and 608 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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