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 agentmods add skills/navig-run/core/summarizenpx skills add navig-run/core --skill summarizegit clone --depth 1 https://github.com/navig-run/coreWrote 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/navig-run/core/summarize)<a href="https://agentmods.dev/skills/navig-run/core/summarize"><img src="https://agentmods.dev/badge/skills/navig-run/core/summarize.svg" alt="Measured on agentmods" 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 | $0.00102 | $0.00632 |
| Opus 5 | $0.00051 | $0.00316 |
| Sonnet 5 | $0.00020 | $0.00126 |
| Haiku 4.5 | $0.00010 | $0.00063 |
Grade A, and why
Content Summarizer 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 yesterday.
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.
The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
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.
- yesterday First seen · 84 lines · 102 tokens per session scan A 78ce8960b8a4
Content Summarizer is a skill published in the GitHub repository navig-run/core (5 stars, last pushed 19d ago), with no licence file. It adds 102 tokens to every session and 632 once invoked, about $0.0005 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.
Other skills, from other repositories
summarize
Summarize a block of text into a short abstract.
pdf-extraction
Extract text, tables, and metadata from PDFs using pdfplumber.
building-attack-pattern-library-from-cti-reports
Extract and catalog attack patterns from cyber threat intelligence reports into a structured STIX-based library mapped to MITRE ATT&CK for detection engineering and threat-informed defense.
text-statistics
Compute readability and structural statistics for a block of text: word count, sentence count, character count, average word length, and an approximate Flesch reading-ease score. Trigger when the user asks to analyze text, count words, measure readability, or get text statistics.
humanizer
| Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague…
humanizer_zh
| 去除文本中的 AI 生成痕迹。适用于编辑或审阅文本,使其听起来更自然、更像人类书写。 基于维基百科的"AI 写作特征"综合指南。检测并修复以下模式:夸大的象征意义、 宣传性语言、以 -ing 结尾的肤浅分析、模糊的归因、破折号过度使用、三段式法则、 AI 词汇、否定式排比、过多的连接性短语。.