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 market-microstructure-traditionalgit 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/market-microstructure-traditional)<a href="https://agentmods.dev/skills/agiprolabs/claude-trading-skills/market-microstructure-traditional"><img src="https://agentmods.dev/badge/skills/agiprolabs/claude-trading-skills/market-microstructure-traditional/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/market-microstructure-traditional"><img src="https://agentmods.dev/badge/skills/agiprolabs/claude-trading-skills/market-microstructure-traditional.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00040 | $0.02805 |
| Opus 5 | $0.00020 | $0.01403 |
| Sonnet 5 | $0.00008 | $0.00561 |
| Haiku 4.5 | $0.00004 | $0.00281 |
Grade A, and why
market-microstructure-traditional 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 13d 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 — 366 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Market Microstructure (Traditional)
Market microstructure studies how orders become trades and how trades become prices. Understanding these mechanics is essential for execution optimization, market making, and detecting informed flow. This skill covers limit order book (LOB) theory as applied to crypto markets on centralized exchanges, and compares LOB mechanics to the AMM-based structure of DEXes.
Core Concepts
| Concept | What It Tells You |
|---|---|
| Bid-ask spread | Cost of immediacy — how much you pay to trade now vs later |
| Price impact | How your order moves the market price |
| Order book imbalance | Short-term directional predictor from queue sizes |
| Adverse selection | Risk of trading against informed counterparties |
| Inventory risk | Market maker exposure from accumulated positions |
| Execution quality | How well your fills compare to a benchmark |
Bid-Ask Spread Decomposition
The bid-ask spread is not a single thing. It decomposes into three components (Roll, 1984; Glosten & Harris, 1988):
- Adverse selection — compensation for trading against informed traders
- Inventory holding — compensation for carrying risk
- Order processing — fixed costs of providing liquidity (fees, infrastructure)
Spread Measures
# Quoted spread: what you see on the order book
quoted_spread = best_ask - best_bid
quoted_spread_bps = (best_ask - best_bid) / midprice * 10_000
# Effective spread: what you actually pay (accounts for price improvement)
effective_half_spread = abs(trade_price - midprice_at_trade)
effective_spread_bps = effective_half_spread / midprice_at_trade * 10_000
# Realized spread: market maker's actual profit (after price moves)
# Measured at trade_price vs midprice N seconds later
realized_spread = trade_sign * (trade_price - midprice_after_delay)
The effective spread matters most for execution quality. The difference between effective and realized spread measures adverse selection — what the market maker loses to informed flow.
What ships with it
5 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.
- 13d ago First seen · 366 lines · 40 tokens per session scan A 0164b87caa8b
market-microstructure-traditional is a skill published in the GitHub repository agiprolabs/claude-trading-skills (356 stars, last pushed 9d ago), licensed MIT. It adds 40 tokens to every session and 2,805 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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