Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/nirholas/three.ws/onchain-metrics-analysisnpx skills add nirholas/three.ws --skill onchain-metrics-analysisgit clone --depth 1 https://github.com/nirholas/three.wsWrote 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/nirholas/three.ws/onchain-metrics-analysis)<a href="https://agentmods.dev/skills/nirholas/three.ws/onchain-metrics-analysis"><img src="https://agentmods.dev/badge/skills/nirholas/three.ws/onchain-metrics-analysis.svg" alt="Measured on agentmods" 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 | $0.00033 | $0.00936 |
| Opus 5 | $0.00016 | $0.00468 |
| Sonnet 5 | $0.00007 | $0.00187 |
| Haiku 4.5 | $0.00003 | $0.00094 |
Grade A, and why
onchain-metrics-analysis 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 6d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
On-Chain Metrics Analysis
When to use this skill
Use when the user asks about:
- On-chain activity for a specific blockchain or token
- Network health and usage trends
- Interpreting on-chain data for investment decisions
- Comparing blockchains by activity metrics
- Detecting accumulation or distribution phases via on-chain signals
Analysis Framework
1. Network Activity Metrics
Assess overall network health:
- Daily active addresses: Unique addresses transacting — trend over 7d, 30d, 90d
- New addresses: Rate of new wallet creation — proxy for user adoption
- Transaction count: Daily transactions and trend; distinguish between value transfers and contract calls
- Transaction volume (USD): Total value moved on-chain
- Average transaction size: Large increases may indicate institutional activity
- Network fees: Total fees paid — reflects organic demand for blockspace
2. Token-Specific Metrics
For individual tokens:
- Holder count: Total unique holders and growth rate
- Holder distribution: Gini coefficient or top-10 holder concentration percentage
- Transfer volume: Token-specific transfer volume and frequency
- Exchange balance: Percentage of supply held on exchanges — declining = accumulation
- Dormancy flow: Ratio of market cap to annualized dormancy — high values suggest older coins moving (potential distribution)
- Velocity: How frequently tokens change hands — high velocity can indicate speculative activity
3. Whale and Smart Money Analysis
Track large wallet behavior:
- Whale wallet threshold: Define what constitutes a "whale" for this token (top 0.1% holders)
- Accumulation signals: Whales moving tokens off exchanges to cold wallets
- Distribution signals: Whales moving tokens to exchanges (potential sell prep)
- Smart money wallets: Track wallets with historical track record of profitable early entries
- Large transaction count: Number of transactions above $100K in 24h
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.
- 6d ago First seen · 96 lines · 33 tokens per session scan A fe0fea53d09d
onchain-metrics-analysis is a skill published in the GitHub repository nirholas/three.ws (110 stars, last pushed today), licensed Apache-2.0. It adds 33 tokens to every session and 936 once invoked, about $0.0002 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 2026-08-30.
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