Borrowing it
Nothing to install: this file belongs to manavaga/web3-signals-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/manavaga/web3-signals-mcp/main/AGENTS.mdgit clone --depth 1 https://github.com/manavaga/web3-signals-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/manavaga/web3-signals-mcp/agents-md)<a href="https://agentmods.dev/instructions/manavaga/web3-signals-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/manavaga/web3-signals-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/manavaga/web3-signals-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/manavaga/web3-signals-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 | $0.01217 | $0.01217 |
| Opus 5 | $0.00609 | $0.00609 |
| Sonnet 5 | $0.00243 | $0.00243 |
| Haiku 4.5 | $0.00122 | $0.00122 |
Grade A, and why
web3-signals-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 8d 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 — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Web3 Signals Agent
Identity
- Name: Web3 Signals Agent
- Description: Multi-agent crypto market intelligence system. Five specialized AI agents analyze whale activity, derivatives positioning, technical indicators, narrative momentum, and market data — fused into scored signals for 20 crypto assets with regime-aware scoring and LLM insights.
- Version: 0.3.0
- Provider: Web3 Signals
Architecture
Web3 Signals is a multi-agent market intelligence system that fuses 5 independent data dimensions into actionable scored signals (0-100).
Signal Generation (every 15 minutes)
- 5 specialized agents independently score each asset (0-100) with continuous proportional scoring — no flat buckets, indicators like RSI, funding rate, and F&G produce proportional scores across their full range
- Direction-aware asymmetric weighting — different weight sets for bullish vs bearish leans, based on per-dimension accuracy data
- Direction gating — zero out dimensions with historically bad accuracy in specific directions (e.g. whale data gated in bullish direction due to 16-27% accuracy)
- Dynamic data reweighting — agents with missing/partial data get reduced weight, redistributed to agents with full data
- Velocity overlay — computes rate-of-change of RSI, MACD, F&G, and funding rate across 1h/4h/24h windows. When indicators are accelerating against the signal (e.g. RSI still falling while system says BUY), dampens the signal by 30-70%. Prevents premature contrarian calls.
- Trend override — in confirmed BTC downtrends (price >5% below 30D MA), contrarian boost on market/derivatives is dampened by 30%, allowing bearish signals to emerge
- Dynamic abstain zone — threshold adjusts based on Fear & Greed: extreme conditions narrow the band (more signals), neutral markets widen it (fewer, better signals)
Scoring Philosophy
Contrarian / mean-reversion: Fear = buying opportunity, greed = danger. When the crowd panics, the system looks for value. When euphoria peaks, it signals caution.
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.
- 8d ago First seen · 88 lines · 1,217 tokens per session scan A 616e2edc6926
web3-signals-mcp AGENTS.md is an instructions file published in the GitHub repository manavaga/web3-signals-mcp (3 stars, last pushed 22d ago), licensed MIT. It adds 1,217 tokens to every session, about $0.0061 per session on Opus 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.
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