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 liquidity-analysisgit 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/liquidity-analysis)<a href="https://agentmods.dev/skills/agiprolabs/claude-trading-skills/liquidity-analysis"><img src="https://agentmods.dev/badge/skills/agiprolabs/claude-trading-skills/liquidity-analysis/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/liquidity-analysis"><img src="https://agentmods.dev/badge/skills/agiprolabs/claude-trading-skills/liquidity-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
- Socket pass
- Snyk warn
SkillSpector: 4 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
- medium Data Exfiltration · line 66 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 325 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 114 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.03738 |
| Opus 5 | $0.00011 | $0.01869 |
| Sonnet 5 | $0.00004 | $0.00748 |
| Haiku 4.5 | $0.00002 | $0.00374 |
Grade A, and why
liquidity-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 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 — 359 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Liquidity Analysis — DEX Depth Assessment for Solana Tokens
Liquidity analysis answers three critical questions before every trade: Can I get in at a reasonable price? Can I get out when I need to? and Is this pool safe? Without it, you risk excessive slippage, failed exits, and rug pulls.
Why Liquidity Analysis Matters
Position sizing: Maximum position size is bounded by available liquidity. A $10K position in a pool with $20K TVL will move the price significantly. Rule of thumb: keep trade size under 2% of pool depth to limit slippage below 1%.
Execution cost: Slippage is a direct cost. On a 5 SOL buy, the difference between 0.3% and 3% slippage is real money lost on every entry and exit.
Rug risk detection: Thin liquidity, single pools, unlocked LP tokens, and newly created pools are warning signs. Liquidity analysis catches these before you enter.
Exit planning: Entry liquidity may differ from exit liquidity. If LP is unlocked and owned by one wallet, it can be pulled at any time.
Key Concepts
Total Value Locked (TVL)
Total value of assets deposited in a pool. For a SOL/TOKEN pool with 100 SOL and 1M TOKEN at $0.01 each, TVL = 100 * SOL_price + 1M * $0.01. TVL alone is insufficient — you need depth at the current price range.
Liquidity Depth
How much can be traded before moving the price X%. In constant-product AMMs, depth is uniform. In concentrated liquidity (CLMM), depth varies by price range — thick near the current price, thin or zero outside active ranges.
Concentration Factor (CLMM)
Concentrated liquidity pools focus capital in a narrow price range, providing deeper liquidity within that range but nothing outside it. A pool with $50K TVL concentrated in a +/-5% range provides the same depth as a $500K constant-product pool within that range, but zero depth beyond it.
Slippage Curve
Slippage is not linear. Plotting slippage against trade size produces a curve that's gentle for small trades and steep for large ones. The shape depends on pool type, TVL, and concentration.
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 · 359 lines · 22 tokens per session scan A f13ef38efce8
liquidity-analysis 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 3,738 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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