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 jingerzz/ai-investment-courses --skill pageindex-rag-coursegit clone --depth 1 https://github.com/jingerzz/ai-investment-coursesWrote 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/jingerzz/ai-investment-courses/pageindex-rag-course)<a href="https://agentmods.dev/skills/jingerzz/ai-investment-courses/pageindex-rag-course"><img src="https://agentmods.dev/badge/skills/jingerzz/ai-investment-courses/pageindex-rag-course/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/jingerzz/ai-investment-courses/pageindex-rag-course"><img src="https://agentmods.dev/badge/skills/jingerzz/ai-investment-courses/pageindex-rag-course.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00166 | $0.01764 |
| Opus 5 | $0.00083 | $0.00882 |
| Sonnet 5 | $0.00033 | $0.00353 |
| Haiku 4.5 | $0.00017 | $0.00176 |
Grade A, and why
pageindex-rag-course 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
pageindex-rag-course
Agent guidance for the course edition of the PageIndex RAG MCP server. The student installs and registers it via the course-setup skill; this skill explains how to use it once it's live.
Server fingerprint
- Server name (in Zo MCP registry):
page-index-rag-course - Tool count: 14
- Source:
professional/servers/page-index-rag-course/ - Entry point:
uv run rag-server - LLM backend: local Ollama at
http://localhost:11434/v1, modelgemma4:e2b - Pre-indexed filings: BLK (10-K + 10-Q × 2) and HOOD (10-K + 10-Q × 3) — at least 7 documents
If the indexed-filing count is 0, route the student back to the course-setup skill — Ollama or the model is likely missing.
When to invoke
The student's question requires reading the text of a public-company SEC filing — financials, risk factors, MD&A, exec comp, ownership, legal, segments. Examples:
- "What are BLK's biggest risk factors in the latest 10-K?"
- "Did HOOD's MD&A discussion change from Q2 to Q3?"
- "What does management say about revenue drivers?"
- "Compare BLK and HOOD on regulatory risk."
Do not invoke for: real-time stock price, breaking news, anything not in a filing. Use the SPY/TLT skill or web search for those.
Pre-indexed starter filings
BLK and HOOD ship pre-indexed (≥7 filings total) so the Week 2 centerpiece exercises work the moment the server is registered — no SEC fetch required, no waiting for indexing. Use them as the default examples.
For any other ticker, fetch_company_filings is fully available from day one. Heads-up to share with the student before they fetch:
- Indexing a full 10-K with
gemma4:e2bsummaries on a Zo box takes ~2–5 minutes per filing —fetch_company_filingsreturns immediately with abatch_id; pollcheck_indexing_statusuntilCOMPLETEbefore searching. - SEC EDGAR rate limit is ~10 req/s; PageIndex stays under that, but back-to-back fetches across many tickers can still hit it. If you do, wait 10 minutes.
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 · 113 lines · 166 tokens per session scan A bafee47068da
pageindex-rag-course is a skill published in the GitHub repository jingerzz/ai-investment-courses (4 stars, last pushed 4mo ago), licensed MIT. It adds 166 tokens to every session and 1,764 once invoked, about $0.0008 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 2026-08-31.
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