Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add nutdnuy/portfolio-optimization-ai-plugin/plugin install portfolio-optimization-ai-pluginWrote 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/commands/nutdnuy/portfolio-optimization-ai-plugin/portfolio-init-run)<a href="https://agentmods.dev/commands/nutdnuy/portfolio-optimization-ai-plugin/portfolio-init-run"><img src="https://agentmods.dev/badge/commands/nutdnuy/portfolio-optimization-ai-plugin/portfolio-init-run.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 | $0.00008 | $0.00261 |
| Opus 5 | $0.00004 | $0.00130 |
| Sonnet 5 | $0.00002 | $0.00052 |
| Haiku 4.5 | $0.00001 | $0.00026 |
Grade A, and why
portfolio-init-run scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Create a portfolio optimization run folder from the user's data and constraints.
First identify:
- whether the CSV contains
returnsorprices - frequency: daily, weekly, monthly, quarterly, or annual
- date column, if any
- assets to include, if a subset is requested
- objective and risk measure, defaulting to
SharpeandMV - long-only or shorting; default long-only
- max single-asset weight; ask only if materially ambiguous
Run a command like:
cd "${CLAUDE_PLUGIN_ROOT:-$PWD}" && python3 scripts/portfolio_optimizer_ai.py init-run \
--name "<portfolio name>" \
--data-path "<csv path>" \
--data-kind returns \
--frequency daily \
--risk-measure MV \
--objective Sharpe \
--max-weight 0.40 \
--output-root outputs
Return the run folder path and summarize the assumptions. Do not run the optimization until dependencies are checked or the user asks for the full flow.
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 · 35 lines · 8 tokens per session scan A f0d348fa24e5
portfolio-init-run is a command published in the GitHub repository nutdnuy/portfolio-optimization-ai-plugin (25 stars, last pushed 2mo ago), licensed MIT. It adds 8 tokens to every session and 261 once invoked, about $0.0000 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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../../../shared/commands/archive-ledger.md.
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