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 ihatesea69/kiro-kit --skill nlp-text-processinggit clone --depth 1 https://github.com/ihatesea69/kiro-kitWrote 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/ihatesea69/kiro-kit/nlp-text-processing)<a href="https://agentmods.dev/skills/ihatesea69/kiro-kit/nlp-text-processing"><img src="https://agentmods.dev/badge/skills/ihatesea69/kiro-kit/nlp-text-processing/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/ihatesea69/kiro-kit/nlp-text-processing"><img src="https://agentmods.dev/badge/skills/ihatesea69/kiro-kit/nlp-text-processing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00031 | $0.00289 |
| Opus 5.5 | $0.00012 | $0.00116 |
| Sonnet 5.5 | $0.00006 | $0.00058 |
| Haiku 4.5 | $0.00003 | $0.00029 |
Grade A, and why
nlp-text-processing 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.
What it actually says
NLP Text Processing
Activate this skill when working with text data and natural language processing.
When to Use
- Text preprocessing and cleaning
- Building text classification models
- Named entity recognition (NER)
- Sentiment analysis pipelines
- Text embedding and similarity search
- Working with Hugging Face transformers
Libraries
- spaCy: Production NLP pipelines
- Hugging Face Transformers: Pre-trained models
- NLTK: Classic NLP tools
- sentence-transformers: Text embeddings
Patterns
from transformers import pipeline
# Quick inference
classifier = pipeline("text-classification", model="distilbert-base-uncased")
result = classifier("This product is amazing!")
# Custom fine-tuning
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
model = AutoModelForSequenceClassification.from_pretrained("bert-base-uncased")
Rules
- Preprocess text consistently (lowercase, tokenize)
- Handle multilingual text explicitly
- Use pre-trained models before training from scratch
- Validate with human evaluation, not just metrics
- Consider computational cost of large language models
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 First seen · 49 lines · 31 tokens per session scan A 0a022cf13f03
nlp-text-processing is a skill published in the GitHub repository ihatesea69/kiro-kit (19 stars, last pushed 2mo ago), licensed MIT. It adds 31 tokens to every session and 289 once invoked, about $0.0001 per session on Opus 5.5. 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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