Borrowing it
Nothing to install: this file belongs to Parad0x-Labs/openclaw-skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Parad0x-Labs/openclaw-skills/main/AGENTS.mdgit clone --depth 1 https://github.com/Parad0x-Labs/openclaw-skillsWrote 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/instructions/parad0x-labs/openclaw-skills/agents-md)<a href="https://agentmods.dev/instructions/parad0x-labs/openclaw-skills/agents-md"><img src="https://agentmods.dev/badge/instructions/parad0x-labs/openclaw-skills/agents-md/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/instructions/parad0x-labs/openclaw-skills/agents-md"><img src="https://agentmods.dev/badge/instructions/parad0x-labs/openclaw-skills/agents-md.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.09967 | $0.09967 |
| Opus 5.5 | $0.03987 | $0.03987 |
| Sonnet 5.5 | $0.01993 | $0.01993 |
| Haiku 4.5 | $0.00997 | $0.00997 |
Grade C, and why
openclaw-skills AGENTS.md scanned grade C with 1 finding 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 23d 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.
Reaches for credential fileshighPrivilege escalation
SSH keys, cloud credentials, git-credentials, .npmrc, /etc/shadow: reading these is how a config file becomes a credential leak.
- **forbidden_path** (critical) — `.ssh/`, `.gnupg/`, `.aws/credentials`, `.kube/config` How it starts
The opening of the file, as written. The whole thing — 895 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Liquefy — AI Agent Interface
You are an AI agent. This file tells you everything you need to operate Liquefy. Read this FIRST. It replaces reading the README, docs, or source code for 95% of tasks.
For what each component does, what has been demonstrated and what is not established, see
REVIEW.md (generated from evidence/claims.json; validate with
node scripts/check-claims-registry.mjs).
One-Line Setup
macOS / Linux:
make setup
Or if make isn't available:
bash install.sh
Windows (PowerShell):
.\setup.ps1
Windows (CMD):
setup.bat
pip install (into existing project):
pip install git+https://github.com/Parad0x-Labs/openclaw-skills.git
Optional extras: pip install "liquefy-openclaw[vision,cloud,anchor,api,all] @ git+https://..."
Docker:
docker compose run liquefy tools/tracevault_pack.py ./data --org default --out ./vault/output --json
All paths create a virtualenv, install dependencies, run a smoke test, and print "READY".
What Liquefy Does
Liquefy compresses, redacts, and vaults AI agent workspace data (session logs, JSONL traces, artifacts, screenshots, memory files). It has 24 specialized compression engines that auto-detect data format and pick the best one. Everything is verified bit-perfect (MRTV — Mandatory Round-Trip Verification).
Quick Commands (Copy-Paste Ready)
All commands work from the repo root after make setup.
Compress a directory into a vault
make quick DIR=./path/to/data
Or explicitly:
python tools/tracevault_pack.py ./path/to/data --org default --out ./vault/output
Compress an OpenClaw workspace
python tools/liquefy_openclaw.py --workspace ~/.openclaw --out ./vault/openclaw --json
Works with any agent framework
Liquefy is framework-agnostic. OpenClaw, NanoClaw, LangChain, CrewAI, Claude Agent SDK, custom scripts — if it writes files, Liquefy handles it. No adapter needed.
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.
- 23d ago Changed · +4 lines · +53 tokens per session f844b6ed3a72
- 2mo ago First seen · 891 lines · 9,914 tokens per session scan C c34dfa8d8620
openclaw-skills AGENTS.md is an instructions file published in the GitHub repository Parad0x-Labs/openclaw-skills (23 stars, last pushed 18d ago), licensed MIT. It adds 9,967 tokens to every session, about $0.0399 per session on Opus 5.5. A static security scan graded it C with 1 finding (reaches for credential files). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.