Borrowing it
Nothing to install: this file belongs to ChainAware/behavioral-prediction-mcp. 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/ChainAware/behavioral-prediction-mcp/main/AGENTS.mdgit clone --depth 1 https://github.com/ChainAware/behavioral-prediction-mcpWrote 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/chainaware/behavioral-prediction-mcp/agents-md)<a href="https://agentmods.dev/instructions/chainaware/behavioral-prediction-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/chainaware/behavioral-prediction-mcp/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/chainaware/behavioral-prediction-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/chainaware/behavioral-prediction-mcp/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 | $0.08761 | $0.08761 |
| Opus 5.5 | $0.03504 | $0.03504 |
| Sonnet 5.5 | $0.01752 | $0.01752 |
| Haiku 4.5 | $0.00876 | $0.00876 |
Grade A, and why
behavioral-prediction-mcp 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.
How it starts
The opening of the file, as written. The whole thing — 506 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ChainAware Subagent Index
Machine-readable index of all 34 Claude Code subagents in .claude/agents/.
Each agent is a specialist that handles a specific Web3 intelligence task using the
ChainAware Behavioral Prediction MCP (https://prediction.mcp.chainaware.ai/sse).
🏆 Featured in the CB Insights Fraud Prevention Market Map for the AI Era (2026) 🌐 Listed on the BNB Chain AI Landscape (2025) 🚀 Listed on BNB Chain Kickstart — Marketing Tools (2025) 💰 Awarded a $250k Google Cloud Grant (2025) ☁️ Accepted into the AWS Fintech Accelerator (2024) 🌱 Featured in the Safary Club Web3 Growth Landscape — Growth Tools (2024)
Links: Website · Twitter · LinkedIn · Blog · Learn · Examples
Accuracy: 98% Fraud Detection · 90.1% Rug Pull Detection — backtesting verified
Quick setup:
claude mcp add --transport sse chainaware-behavioral-prediction \
https://prediction.mcp.chainaware.ai/sse --header "X-API-Key: YOUR_KEY"
export CHAINAWARE_API_KEY="your-key-here"
Agent Directory
chainaware-wallet-auditor
File: .claude/agents/chainaware-wallet-auditor.md
Model: claude-sonnet-4-6
Tools: predictive_behaviour
Purpose: Full due diligence. Deep behavioural analysis of a wallet including fraud signals, intent, experience, and recommendations.
Triggers: "full audit of 0x...", "due diligence on this wallet", "complete analysis", "deep dive on this address"
Input: wallet address + network
Output: Behaviour profile, fraud signals, experience score, intent, recommendations
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 · 506 lines · 8,761 tokens per session scan A 4e2af6c0b1a4
behavioral-prediction-mcp AGENTS.md is an instructions file published in the GitHub repository ChainAware/behavioral-prediction-mcp (10 stars, last pushed 2mo ago), licensed MIT. It adds 8,761 tokens to every session, about $0.0350 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.