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 vahidkaargar/it-department-skills --skill sample-skillgit clone --depth 1 https://github.com/vahidkaargar/it-department-skillsWrote 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/vahidkaargar/it-department-skills/sample-skill)<a href="https://agentmods.dev/skills/vahidkaargar/it-department-skills/sample-skill"><img src="https://agentmods.dev/badge/skills/vahidkaargar/it-department-skills/sample-skill/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/vahidkaargar/it-department-skills/sample-skill"><img src="https://agentmods.dev/badge/skills/vahidkaargar/it-department-skills/sample-skill.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 | $0.00000 | $0.01103 |
| Opus 5 | $0.00000 | $0.00551 |
| Sonnet 5 | $0.00000 | $0.00221 |
| Haiku 4.5 | $0.00000 | $0.00110 |
Grade A, and why
sample-skill 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 11d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- sample-text-processor — 88% identical, 11 lines differ
How it starts
The opening of the file, as written. The whole thing — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sample Text Processor
Name: sample-text-processor Tier: BASIC Category: Text Processing Dependencies: None (Python Standard Library Only) Author: Claude Skills Engineering Team Version: 1.0.0 Last Updated: 2026-02-16
Description
The Sample Text Processor is a simple skill designed to demonstrate the basic structure and functionality expected in the claude-skills ecosystem. This skill provides fundamental text processing capabilities including word counting, character analysis, and basic text transformations.
This skill serves as a reference implementation for BASIC tier requirements and can be used as a template for creating new skills. It demonstrates proper file structure, documentation standards, and implementation patterns that align with ecosystem best practices.
The skill processes text files and provides statistics and transformations in both human-readable and JSON formats, showcasing the dual output requirement for skills in the claude-skills repository.
Features
Core Functionality
- Word Count Analysis: Count total words, unique words, and word frequency
- Character Statistics: Analyze character count, line count, and special characters
- Text Transformations: Convert text to uppercase, lowercase, or title case
- File Processing: Process single text files or batch process directories
- Dual Output Formats: Generate results in both JSON and human-readable formats
Technical Features
- Command-line interface with comprehensive argument parsing
- Error handling for common file and processing issues
- Progress reporting for batch operations
- Configurable output formatting and verbosity levels
- Cross-platform compatibility with standard library only dependencies
Usage
Basic Text Analysis
python text_processor.py analyze document.txt
python text_processor.py analyze document.txt --output results.json
Text Transformation
python text_processor.py transform document.txt --mode uppercase
python text_processor.py transform document.txt --mode title --output transformed.txt
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 163 lines · 0 tokens per session scan A 8365a36db737
sample-skill is a skill published in the GitHub repository vahidkaargar/it-department-skills (2 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,103 tokens. 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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