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-072git 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-072)<a href="https://agentmods.dev/skills/legendtkl/agentic-skill-router/skill-072"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-072/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-072"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-072.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 | $0.00035 | $0.00334 |
| Opus 5 | $0.00017 | $0.00167 |
| Sonnet 5 | $0.00007 | $0.00067 |
| Haiku 4.5 | $0.00003 | $0.00033 |
Grade A, and why
skill-072 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 6d 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
Office File Management
Overview
In today's digital workspace, managing office files is essential for productivity and organization. This skill encompasses techniques for handling various office documents, including Word, Excel, and PowerPoint files.
File Organization
Structuring Directories
Effective file management starts with a well-organized directory structure:
- Create separate folders for different projects.
- Use meaningful file names to indicate the content.
- Regularly archive old files to keep your workspace tidy.
File Version Control
Keeping track of different versions of documents is crucial:
- Utilize cloud storage solutions that offer version history.
- Regularly save backups of critical documents.
File Conversion Techniques
Converting Between Formats
You may need to convert files between formats:
- Use online conversion tools or built-in functionality in software such as Word or Excel.
- For programmatic conversion, libraries like
python-docxfor Word andpython-pptxfor PowerPoint can be used.
Example: Convert DOCX to PDF
from docx import Document
# Load the Word document
doc = Document('example.docx')
# Save as PDF (requires additional library like pypdf)
doc.save('example.pdf')
Conclusion
Efficient office file management promotes better collaboration and productivity. By implementing robust organizational strategies and leveraging available tools, users can streamline their workflow.
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.
- 6d ago First seen · 42 lines · 35 tokens per session scan A d51a99afbb67
skill-072 is a skill published in the GitHub repository legendtkl/agentic-skill-router (5 stars, last pushed 3mo ago), licensed MIT. It adds 35 tokens to every session and 334 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 2026-09-03.
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