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 Morningstar202604/awesome-skillkit --skill sample-skillgit clone --depth 1 https://github.com/Morningstar202604/awesome-skillkitWrote 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/morningstar202604/awesome-skillkit/sample-skill)<a href="https://agentmods.dev/skills/morningstar202604/awesome-skillkit/sample-skill"><img src="https://agentmods.dev/badge/skills/morningstar202604/awesome-skillkit/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/morningstar202604/awesome-skillkit/sample-skill"><img src="https://agentmods.dev/badge/skills/morningstar202604/awesome-skillkit/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 | $0.00033 | $0.01157 |
| Opus 5.5 | $0.00013 | $0.00463 |
| Sonnet 5.5 | $0.00007 | $0.00231 |
| Haiku 4.5 | $0.00003 | $0.00116 |
Grade A, and why
sample-text-processor 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 1mo 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.
This is a copy
88% identical to sample-skill — 142 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 173 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
- Updated: 2026-02-16
Introduction
Sample Text Processor is a simple demonstration skill that shows the basic structure and functionality a skill should have in the claude-skills ecosystem. It provides basic text-processing capabilities, including word-count statistics, character analysis, and basic text transforms.
This skill is a reference implementation of the BASIC-tier requirements and can be used as a template for creating new skills. It demonstrates the file structure, documentation standards, and implementation patterns that follow ecosystem best practices.
The skill processes text files and outputs statistics and transform results in both human-readable and JSON formats, reflecting the claude-skills repo's requirement that skills support dual output formats.
Features
Core functionality
- Word-count analysis: total words, unique words, and word frequency
- Character statistics: character count, line count, and special characters
- Text transforms: convert to uppercase, lowercase, or title case
- File processing: process a single text file or batch-process a directory
- Dual output formats: supports both JSON and human-readable output
Technical features
- A command-line interface with full argument parsing
- Error handling covering common file and processing problems
- Progress reporting for batch operations
- Configurable output format and verbosity
- Standard-library only, cross-platform
Usage
Basic text analysis
python text_processor.py analyze assets/sample_text.txt
python text_processor.py --output results.json analyze assets/sample_text.txt
Text transforms
python text_processor.py transform assets/sample_text.txt --mode upper
python text_processor.py --output transformed.txt transform assets/sample_text.txt --mode title
What ships with it
5 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.
- 1mo ago Changed · -5 lines 13fd9eb51b42
- 1mo ago Changed 7dcb28450525
- 1mo ago Changed · +4 lines 514bc839e7c6
- 1mo ago First seen · 174 lines · 33 tokens per session scan A b5b8d4d21daf
sample-text-processor is a skill published in the GitHub repository Morningstar202604/awesome-skillkit (0 stars, last pushed 25d ago), licensed Apache-2.0. It adds 33 tokens to every session and 1,157 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to sample-skill, differing in 142 lines, and is treated as a copy.
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