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/Zyrexnn/Cybermesnpx agentmods add commands/zyrexnn/cybermes/token-scanWrote 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/commands/zyrexnn/cybermes/token-scan)<a href="https://agentmods.dev/commands/zyrexnn/cybermes/token-scan"><img src="https://agentmods.dev/badge/commands/zyrexnn/cybermes/token-scan/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/commands/zyrexnn/cybermes/token-scan"><img src="https://agentmods.dev/badge/commands/zyrexnn/cybermes/token-scan.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 | $0.00000 | $0.01334 |
| Opus 5.5 | $0.00000 | $0.00534 |
| Sonnet 5.5 | $0.00000 | $0.00267 |
| Haiku 4.5 | $0.00000 | $0.00133 |
Grade A, and why
token-scan 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 1mo 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 token-scan — 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: token-scan description: Meme coin and token security scan — checks for rug pull vectors (hidden mint, honeypot, fee manipulation, LP lock bypass, authority retention, bonding curve exploits, fake renounce, sandwich amplification). Manual 8-class grep audit (with an optional automated scanner if present). Usage: /token-scan <contract_path_or_dir> [--chain solana]
/token-scan
Fast rug pull detection for meme coins and token contracts. Covers EVM (Solidity) and Solana (Rust/Anchor).
Usage
/token-scan contracts/Token.sol # Single EVM contract
/token-scan src/ --recursive # Scan entire directory
/token-scan programs/token/ --chain solana --recursive # Solana program
/token-scan contracts/Token.sol --output findings/report.md # Save report
Step 0: Quick Kill Signals
Before scanning code, check:
[ ] Contract is verified (source code available)?
[ ] Deployer has no rug history?
[ ] Token has been trading > 1 hour?
[ ] Liquidity > $5K?
[ ] Not a proxy with retained admin?
If ANY answer is NO → flag and proceed with extreme caution.
Step 1: Optional Automated Scanner
Optional accelerator — not bundled by default. If you have a local
token_scanner.py(or any rug-vector scanner) on PATH, run it first for a quick risk score. If you don't, skip straight to Step 2 — the manual 8-class grep audit below is the real, self-contained check and needs no extra tooling.
# If present:
python3 tools/token_scanner.py <contract_path> # EVM
python3 tools/token_scanner.py <program_dir> --chain solana --recursive # Solana
The manual audit (Steps 2-9) covers all 8 bug classes via grep and is sufficient on its own.
Step 2: Hidden Mint Check
grep -rn "function mint\|_mint(\|_balances\[.*\] +=" src/ --include="*.sol" | grep -v "test\|lib"
grep -rn "delegatecall" src/ --include="*.sol"
# Solana:
grep -rn "MintTo\|mint_to\|mint_authority" src/ --include="*.rs"
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.
- 1mo ago First seen · 141 lines · 0 tokens per session scan A 1dcb13bb9d14
token-scan is a command published in the GitHub repository Zyrexnn/Cybermes (668 stars, last pushed 1mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,334 tokens. A static security scan graded it A with 0 findings. It is 100% identical to token-scan, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
token-scan
Meme coin and token security scan — checks for rug pull vectors (hidden mint, honeypot, fee manipulation, LP lock bypass, authority retention, bonding curve exploits, fake renounce, sandwich amplification). Manual 8-class grep audit (with an optional automated scanner if present). Usage: /token-scan [--chain solana].
sicario.assess
Assess the repository against SicarioSpec guardrails.
sicario.review
Review the active spec, plan, tasks, staged changes, or branch for security and governance gaps.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.