Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/clawd-aftermath/nunchi-for-aftermathnpx agentmods add skills/clawd-aftermath/nunchi-for-aftermath/onboardWrote 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/clawd-aftermath/nunchi-for-aftermath/onboard)<a href="https://agentmods.dev/skills/clawd-aftermath/nunchi-for-aftermath/onboard"><img src="https://agentmods.dev/badge/skills/clawd-aftermath/nunchi-for-aftermath/onboard/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/skills/clawd-aftermath/nunchi-for-aftermath/onboard"><img src="https://agentmods.dev/badge/skills/clawd-aftermath/nunchi-for-aftermath/onboard.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 | $0.00017 | $0.02284 |
| Opus 5 | $0.00009 | $0.01142 |
| Sonnet 5 | $0.00003 | $0.00457 |
| Haiku 4.5 | $0.00002 | $0.00228 |
Grade A, and why
agent-onboarding 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 9d 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.
This is a copy
100% identical to agent-onboarding — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 316 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Onboarding
Complete first-time setup for the YEX autonomous trading system on Hyperliquid. Follow every step in order. Do not skip steps. Verify each step before proceeding to the next.
Agent Mandate
You are onboarding onto the YEX trading system. Your goal is to reach a state where you can autonomously trade on Hyperliquid (testnet or mainnet). Every step has a verification command — if verification fails, fix the issue before continuing.
RULES:
- Follow steps sequentially — each depends on the previous
- NEVER skip builder fee approval — all orders will fail without it
- ALWAYS validate with a mock trade before going live
- NEVER start on mainnet without completing testnet validation first
- Save all credentials (passwords, addresses) — they cannot be recovered
Step 1: Environment Bootstrap
Install Python dependencies and verify the CLI works.
Option A — Shell script (recommended):
cd ~/agent-cli
bash scripts/bootstrap.sh
Option B — Manual:
cd ~/agent-cli
python3 -m venv .venv
source .venv/bin/activate
pip install -e .
Verify:
hl setup check
Expected: All items show OK, no !! issues (except missing key — that's Step 2).
If fails:
| Error | Fix |
|---|---|
python3 not found |
Install Python 3.10+ via brew install python or system package manager |
pip install failed |
Ensure you're in a venv: source .venv/bin/activate |
ModuleNotFoundError: hyperliquid |
Run pip install hyperliquid-python-sdk |
Step 2: Wallet Setup
Create or import a Hyperliquid wallet.
Decision tree:
- Do you have a private key?
- YES → Import it:
hl wallet import --key 0x<your_key> - NO → Create a new one (non-interactive, with auto-saved credentials):
This creates the wallet, saveshl wallet auto --save-env --jsonHL_KEYSTORE_PASSWORDto~/.hl-agent/env(auto-detected by CLI), and outputs JSON:{"address": "...", "password": "...", "keystore": "...", "env_file": "..."}.
- YES → Import it:
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.
- 9d ago First seen · 316 lines · 17 tokens per session scan A 989fee88c5e4
agent-onboarding is a skill published in the GitHub repository clawd-aftermath/nunchi-for-aftermath (2 stars, last pushed 21d ago), licensed MIT. It adds 17 tokens to every session and 2,284 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to agent-onboarding, differing in 0 lines, and is treated as a copy.
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