FORGE-data-compression

FORGE-data-compression is a skill for Claude Code, Codex from ariffazil/AAA. It costs 79 tokens per session (424 once invoked), scanned A, original, AGPL-3.0.

A method for shortening long logs, code extracts, and evidence bundles so they fit within an AI assistant's context limit while retaining important meaning. The input describes chunking and summarising, including streaming workflows.

In plain words
What is it for?
Use it to compress logs, code dumps, and multi-source evidence before sending them to an agent or running a chunk-and-summarise pipeline.
Why use it?
Large inputs can exceed the amount of text an AI assistant can consider at once, causing useful details to be dropped or preventing processing altogether.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit Use it to compress logs, code dumps, and multi-source evidence before sending them to an agent or running a chunk-and-summarise pipeline.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ariffazil/aaa/forge-data-compression
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.

Any agent
npx skills add ariffazil/AAA --skill forge-data-compression
Clone the repo
git clone --depth 1 https://github.com/ariffazil/AAA

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 FORGE-data-compression

README.md
[![agentmods](https://agentmods.dev/badge/skills/ariffazil/aaa/forge-data-compression/github.svg)](https://agentmods.dev/skills/ariffazil/aaa/forge-data-compression)
Your own site
<a href="https://agentmods.dev/skills/ariffazil/aaa/forge-data-compression"><img src="https://agentmods.dev/badge/skills/ariffazil/aaa/forge-data-compression/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.

agentmods 80×15 button for FORGE-data-compression

Your own site · 80×15
<a href="https://agentmods.dev/skills/ariffazil/aaa/forge-data-compression"><img src="https://agentmods.dev/badge/skills/ariffazil/aaa/forge-data-compression.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 79 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 424 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00079 $0.00424
Opus 5.5 $0.00032 $0.00170
Sonnet 5.5 $0.00016 $0.00085
Haiku 4.5 $0.00008 $0.00042

Measured 3d ago against content hash 3844ff2b6e57, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

FORGE-data-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 3d 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.

skills/FORGE-data-compression/SKILL.md · 45 lines

The source is not reproduced here

Licensed AGPL-3.0

The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

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. 3d ago First seen · 45 lines · 79 tokens per session scan A 3844ff2b6e57

Subscribe to this mod's changes

FORGE-data-compression is a skill published in the GitHub repository ariffazil/AAA (0 stars, last pushed yesterday), licensed AGPL-3.0. It adds 79 tokens to every session and 424 once invoked, about $0.0003 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 2026-10-30.

Related

Other skills, from other repositories

agentlas-auto-activation

Use when adding or auditing local runtime behavior that turns a project folder into an Agentlas-aware workspace with .agentlas memory and sitemap files.

agentlas-ai/Agentlas-OS · 34 tokens

pm-soul

Use when preserving product intent, acceptance criteria, decision memory, open loops, roadmap context, or the product-manager continuity layer of an agent team.

agentlas-ai/Agentlas-OS · 33 tokens

compass-integrity

Use when the user is about to rely on prior session memory for a non-trivial decision, or when something feels off about a recall hit — runs the Merkle chain check, drift summary, and daemon liveness in one pass and surfaces any tampering, drift bursts, or daemon-down state before the user acts on stale or corrupted…

chunxiaoxx/nautilus-compass · 74 tokens

nautilus-compass-memory

Local-first long-term memory for AI agents via MCP — zero LLM calls at write time, typed retrieval at read time. Use when session decisions and pitfalls should survive across days, when multiple agents or dialogs share facts on the same filesystem, or when you want drift detection so past mistakes don't repeat.…

chunxiaoxx/nautilus-compass · 90 tokens

context-engineering

Use this skill to systematically manage what information goes into an LLM context window — selecting, compressing, and prioritizing content to maximize response quality within token budget constraints. Activates when building or optimizing LLM applications, RAG systems, or agent workflows that face context window…

karthikrshet/aiskills · 73 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens