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 AlgoChains/algochains-mcp-server --skill portfolio-optimizegit clone --depth 1 https://github.com/AlgoChains/algochains-mcp-serverWrote 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/algochains/algochains-mcp-server/portfolio-optimize)<a href="https://agentmods.dev/skills/algochains/algochains-mcp-server/portfolio-optimize"><img src="https://agentmods.dev/badge/skills/algochains/algochains-mcp-server/portfolio-optimize.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 | $0.00000 | $0.00486 |
| Opus 5 | $0.00000 | $0.00243 |
| Sonnet 5 | $0.00000 | $0.00097 |
| Haiku 4.5 | $0.00000 | $0.00049 |
Grade A, and why
portfolio-optimize 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 7d 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.
What it actually says
portfolio-optimize
Tier: 1 (research, no live money)
Trigger: Monthly, on-demand for subscriber portfolio recommendations
MCP Tool: run_algoclaw_skill("portfolio-optimize", {"bots":["MNQ","CL","MES","NQ"],"capital":50000})
Source Pattern: Riskfolio-Lib HRP + PyPortfolioOpt
What It Does
Computes optimal capital allocation across AlgoChains bots using:
- HRP (Hierarchical Risk Parity) — groups correlated bots, allocates inversely to risk
- Min-Variance — minimizes portfolio volatility for given return target
- Conservative dual — takes minimum weight per bot across both methods
Input
- Bot performance history (pulled from live logs or Supabase)
- Correlation matrix between bot returns
- Subscriber's risk tolerance and capital
Algorithm (pure Python, no Riskfolio dependency required)
# Pure HRP implementation using scipy + numpy
# 1. Compute correlation matrix from bot return histories
# 2. Build hierarchical linkage tree (Ward / single)
# 3. Recursive bisection: allocate capital proportional to cluster variance
# 4. Apply min 5% / max 40% per-bot constraints
Output
{
"capital": 50000,
"method": "HRP",
"allocations": {
"MNQ": {"weight": 0.38, "capital_usd": 19000, "sharpe": 4.61},
"CL": {"weight": 0.28, "capital_usd": 14000, "sharpe": 2.8},
"MES": {"weight": 0.18, "capital_usd": 9000, "sharpe": 2.1},
"NQ": {"weight": 0.16, "capital_usd": 8000, "sharpe": 2.3}
},
"portfolio_sharpe_est": 3.2,
"correlation_note": "MNQ+NQ 96% correlated — HRP auto-reduces both",
"rebalance_frequency": "monthly"
}
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.
- 7d ago First seen · 48 lines · 0 tokens per session scan A 47db2b4daa4f
portfolio-optimize is a skill published in the GitHub repository AlgoChains/algochains-mcp-server (1 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 486 tokens. 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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