compression

compression is a skill for Claude Code, Codex from kalyvask/winning-writing. It costs 184 tokens per session (3,071 once invoked), scanned A, original, MIT.

A writing editor that shortens drafts either to a chosen word count or by removing repeated ideas and unnecessary phrases.

In plain words
What is it for?
Use it to cut cold emails, opinion pieces, product summaries, and other drafts to a target length, or to remove redundancy.
Why use it?
It helps preserve the main substance when a draft is too long or contains wording that says the same thing twice.

Skill for Claude CodeCodex

Part of the winning-writing plugin — 32 skills shipped together

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/kalyvask/winning-writing/compression
Any agent
npx skills add kalyvask/winning-writing --skill compression
Clone the repo
git clone --depth 1 https://github.com/kalyvask/winning-writing

Made for: Claude Code, Codex.

Or install winning-writing, the plugin that ships this one along with the rest of its 32 skills.

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 compression

README.md
[![agentmods](https://agentmods.dev/badge/skills/kalyvask/winning-writing/compression.svg)](https://agentmods.dev/skills/kalyvask/winning-writing/compression)
Your own site
<a href="https://agentmods.dev/skills/kalyvask/winning-writing/compression"><img src="https://agentmods.dev/badge/skills/kalyvask/winning-writing/compression.svg" alt="Measured on agentmods" height="20"></a>
Per session 184 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,071 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original 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 $0.00184 $0.03071
Opus 5 $0.00092 $0.01536
Sonnet 5 $0.00037 $0.00614
Haiku 4.5 $0.00018 $0.00307

Measured 5d ago against content hash d55f4c80c8c5, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

compression 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 5d 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.

side-panel-coach/rules/skills/compression/SKILL.md · 313 lines

How it starts

The opening of the file, as written. The whole thing — 313 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Compression

Source: points/core-rules.md rule 5 (be shorter), points/banned-jargon.md (wordy phrases), points/frameworks.md (six-word summary), and the Kramon in-class redundancy exercise.

"Be shorter. Always. Cut without losing substance." — Kramon

What this skill does

Two modes behind one skill. They cut different things:

Mode Cuts Use when
target-count throat-clearing, hedges, weak sentences, anything between the draft and the word target User has a length to hit (200 for cold email, 500 for op-ed, 6 for product summary)
redundancy phrases where one half is implied by the other (going forward, as I mentioned, reduce so they are smaller, free gift, definitely commit) Draft is wordy in a way that's hard to point at — long without obvious filler

Default --mode both runs redundancy first (it's surgical, every cut is defensible), then target-count (which may need to cut substantive material). The order matters: redundancy cuts free words first, so target-count doesn't have to.

How to invoke

/compression "draft text"
/compression --mode target-count --target-words 200 "draft text"
/compression --mode redundancy "draft text"
/compression --mode both --target-words 500 "draft text"

Without --mode, default to both. --target-words is required for target-count mode and optional for both (if omitted in both, run redundancy only).


Mode 1 — target-count

Most drafts can lose 30% with no loss of meaning. Many can lose 50%. Forced compression is what reveals which sentences were actually carrying weight.

Three drill levels

Level 1 — Cut 30% (standard pass)

Tactics:

  • Remove every -ly adverb that isn't doing real work
  • Replace wordy phrases (see banned-jargon.md)
  • Combine sentences that share a subject
  • Cut hedges: "I think," "perhaps," "it might be the case that"
  • Cut throat-clearing: "In this piece I'll argue that…" — just argue it
  • Replace passive with active

Read the full file on GitHub · 313 lines

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. 5d ago First seen · 313 lines · 184 tokens per session scan A d55f4c80c8c5

Subscribe to this mod's changes

compression is a skill published in the GitHub repository kalyvask/winning-writing (13 stars, last pushed 3d ago), licensed MIT. It adds 184 tokens to every session and 3,071 once invoked, about $0.0009 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 2026-08-30.

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