Borrowing it
Nothing to install: this file belongs to MrWizardlyLoaf/rugcheck-ai. 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/MrWizardlyLoaf/rugcheck-ai/main/AGENTS.mdgit clone --depth 1 https://github.com/MrWizardlyLoaf/rugcheck-aiWrote 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/mrwizardlyloaf/rugcheck-ai/agents-md)<a href="https://agentmods.dev/instructions/mrwizardlyloaf/rugcheck-ai/agents-md"><img src="https://agentmods.dev/badge/instructions/mrwizardlyloaf/rugcheck-ai/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/mrwizardlyloaf/rugcheck-ai/agents-md"><img src="https://agentmods.dev/badge/instructions/mrwizardlyloaf/rugcheck-ai/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 | $0.00511 | $0.00511 |
| Opus 5.5 | $0.00204 | $0.00204 |
| Sonnet 5.5 | $0.00102 | $0.00102 |
| Haiku 4.5 | $0.00051 | $0.00051 |
Grade A, and why
rugcheck-ai AGENTS.md 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.
What it actually says
RugCheck AI — agent guide
On-chain token-safety MCP for Solana. Screen a token for rug/honeypot traps before trading, then execute the buy — re-screened, and routed through Jupiter with a small Jito tip for inclusion. The execution tool returns an unsigned transaction; you sign it, the server never holds keys.
Connect (no install)
Remote MCP endpoint (Streamable HTTP):
https://web-production-58d585.up.railway.app/mcp
Listed on the official MCP Registry as io.github.MrWizardlyLoaf/rugcheck-ai.
Tools
scan_token(mint)— full safety report in one call (verdict, 0–100 score, all risks)is_safe(mint)— quick yes/no gate: one boolean before tradingverify_token_safety(mint)— on-chain audit: mint/freeze authority + Token-2022 trapscheck_authorities(mint)— authority + extension detectionsimulate_sell(mint)— can the token be sold? (honeypot check)simulate_trade(mint, amount_usd)— round-trip buy→sell: real entry/exit cost & loss %check_liquidity(mint)— DEX liquidity, 24h volume, pair ageholders_breakdown(mint)— top-holder concentration (dump risk)token_age(mint)— freshness + real trading activityrug_forecast(mint)— heuristic rug probability + urgency windowscammer_dna(mint)— intent score (0–100) from structural scam signalscheck_deployer(mint)— the wallets holding power over the tokencompare_tokens(mints)— rank a basket of tokens safest-firstbatch_scan(mints)— scan up to 10 tokens at once, one report eachexecute_safe_swap(mint, wallet, amount_usd)— re-screens, returns an unsigned USDC→token swap to sign
Source & stack
Built with Python (FastMCP). Entry point: server.py. The screening tools are read-only —
they call Solana getAccountInfo and never touch your keys.
Self-host
pip install -r requirements.txt
SOLANA_RPC=<your-rpc-url> python server.py
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 · 46 lines · 511 tokens per session scan A e2edc63727f9
rugcheck-ai AGENTS.md is an instructions file published in the GitHub repository MrWizardlyLoaf/rugcheck-ai (1 stars, last pushed 4mo ago), licensed MIT. It adds 511 tokens to every session, about $0.0020 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 2026-08-31.
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).
vscode model-prompts.instructions.md
Model-specific prompt authoring and registry guidelines.