summarize

summarize is a skill for Claude Code, Codex from cognis-digital/skillhub. It costs 16 tokens per session (115 once invoked), scanned A, original, no licence file.

A text-shortening tool that turns a block of writing into a brief abstract.

In plain words
What is it for?
Use it to condense documents, notes, articles, or other supplied text.
Why use it?
It reduces the time needed to understand long text while retaining its main point.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/cognis-digital/skillhub/summarize
Any agent
npx skills add cognis-digital/skillhub --skill summarize
Clone the repo
git clone --depth 1 https://github.com/cognis-digital/skillhub

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for summarize

README.md
[![agentmods](https://agentmods.dev/badge/skills/cognis-digital/skillhub/summarize.svg)](https://agentmods.dev/skills/cognis-digital/skillhub/summarize)
Your own site
<a href="https://agentmods.dev/skills/cognis-digital/skillhub/summarize"><img src="https://agentmods.dev/badge/skills/cognis-digital/skillhub/summarize.svg" alt="Measured on agentmods" height="20"></a>
Per session 16 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 115 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00016 $0.00115
Opus 5 $0.00008 $0.00057
Sonnet 5 $0.00003 $0.00023
Haiku 4.5 $0.00002 $0.00012

Measured 4d ago against content hash fdbcf328cb61, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

summarize 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 4d 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.

demos/01-basic/registry/summarize/SKILL.md · 18 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Changes

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.

  1. 4d ago First seen · 18 lines · 16 tokens per session scan A fdbcf328cb61

Subscribe to this mod's changes

summarize is a skill published in the GitHub repository cognis-digital/skillhub (0 stars, last pushed 2mo ago), with no licence file. It adds 16 tokens to every session and 115 once invoked, about $0.0001 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 2026-08-31.

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