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-062git 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-062)<a href="https://agentmods.dev/skills/legendtkl/agentic-skill-router/skill-062"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-062/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-062"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-062.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 | $0.00042 | $0.00432 |
| Opus 5 | $0.00021 | $0.00216 |
| Sonnet 5 | $0.00008 | $0.00086 |
| Haiku 4.5 | $0.00004 | $0.00043 |
Grade A, and why
skill-062 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
PDF Merger
Overview
The PDF Merger skill allows users to combine multiple PDF files into one document. This is particularly useful for organizations that need to consolidate reports, presentations, or any other type of documentation into a single file for distribution.
Workflow Decision Tree
Merging PDFs
Use the "Combining multiple PDF files" workflow below.
Combining Multiple PDF Files
To merge PDF files, you can use the PyPDF2 library, which provides an easy-to-use interface for handling PDF files in Python.
Prerequisites
Ensure you have the PyPDF2 library installed. If it’s not installed, you can add it using pip:
pip install PyPDF2
Merging Process
Here is a step-by-step process for merging PDF files:
- Gather PDF Files: Collect all the PDF files you wish to merge.
- Create a merger object: Use the PdfMerger class to start the merging process.
- Append PDFs: Loop through each PDF file and append it to your merger object.
- Write out the merged PDF: Specify the output file name and save the merged PDF.
Sample Code
Here is a simple example:
from PyPDF2 import PdfMerger
# Initialize the PdfMerger
merger = PdfMerger()
# List of PDF files to merge
pdf_files = ['file1.pdf', 'file2.pdf', 'file3.pdf']
# Append each PDF file
for pdf in pdf_files:
merger.append(pdf)
# Write out the merged PDF
merger.write('merged_output.pdf')
merger.close()
Conclusion
This PDF Merger skill simplifies the process of combining multiple PDF documents, providing an efficient solution for users needing to consolidate their files.
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 · 55 lines · 42 tokens per session scan A a9cb0766e53c
skill-062 is a skill published in the GitHub repository legendtkl/agentic-skill-router (5 stars, last pushed 3mo ago), licensed MIT. It adds 42 tokens to every session and 432 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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Use direct Python execution for reliable document creation including spreadsheets, PDFs, and structured reports.
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Convert a PDF, scan, image of a page, or office file to clean markdown through the connected Superlinked MCP edge, so the source document is not read into model context directly. Use when the user asks to read, parse, OCR, extract from, summarize, or answer questions about a document.