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 skills add agiprolabs/claude-trading-skills --skill token-economicsgit clone --depth 1 https://github.com/agiprolabs/claude-trading-skillsWrote 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/agiprolabs/claude-trading-skills/token-economics)<a href="https://agentmods.dev/skills/agiprolabs/claude-trading-skills/token-economics"><img src="https://agentmods.dev/badge/skills/agiprolabs/claude-trading-skills/token-economics/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/skills/agiprolabs/claude-trading-skills/token-economics"><img src="https://agentmods.dev/badge/skills/agiprolabs/claude-trading-skills/token-economics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket fail
- Snyk warn
- NVIDIA SkillSpector pass
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 | $0.00022 | $0.02588 |
| Opus 5 | $0.00011 | $0.01294 |
| Sonnet 5 | $0.00004 | $0.00518 |
| Haiku 4.5 | $0.00002 | $0.00259 |
Grade A, and why
token-economics 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 12d 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 — 273 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Token Economics
Tokenomics — the study of token supply dynamics, distribution, and value accrual — is one of the most important factors in crypto asset analysis. Supply changes directly affect price: new tokens entering circulation create selling pressure, while burns and locks reduce it. Understanding these dynamics lets you estimate dilution risk, identify overvalued or undervalued tokens, and anticipate price-moving unlock events.
Why Tokenomics Matters
Price is a function of demand and supply. In crypto, supply is programmable and constantly changing:
- A token inflating at 50%/year needs 50% demand growth just to maintain price
- A large unlock releasing 10% of circulating supply in one day often causes 5-20% drawdowns
- Tokens with >80% of supply locked have extreme dilution risk ahead
- Protocols that burn fees can become net deflationary, creating structural price support
Key Supply Concepts
Total Supply vs Circulating Supply
total_supply = maximum tokens that will ever exist (or current total minted)
circulating_supply = tokens currently available for trading
locked_supply = total_supply - circulating_supply
circulating_pct = circulating_supply / total_supply * 100
Market Cap vs Fully Diluted Valuation
market_cap = price * circulating_supply
fdv = price * total_supply
fdv_mcap_ratio = fdv / market_cap
The FDV/MCap ratio measures future dilution risk:
| FDV/MCap | Dilution Risk | Interpretation |
|---|---|---|
| 1.0-1.5 | Low | Most supply already circulating |
| 1.5-3.0 | Moderate | Significant supply still locked |
| 3.0-5.0 | High | Majority of supply not yet released |
| >5.0 | Very High | Token will face massive dilution |
Net Inflation Rate
annual_new_tokens = emissions + vesting_unlocks + rewards
annual_burned = fee_burns + buyback_burns
net_new_tokens = annual_new_tokens - annual_burned
net_inflation_rate = net_new_tokens / circulating_supply * 100 # percent per year
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 273 lines · 22 tokens per session scan A 93e590cb5853
token-economics is a skill published in the GitHub repository agiprolabs/claude-trading-skills (356 stars, last pushed 9d ago), licensed MIT. It adds 22 tokens to every session and 2,588 once invoked, about $0.0001 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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