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 agentmods add skills/optimeta/paideia/course-buildernpx skills add OPTIMETA/PAIDEIA --skill course-buildergit clone --depth 1 https://github.com/OPTIMETA/PAIDEIAWrote 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/optimeta/paideia/course-builder)<a href="https://agentmods.dev/skills/optimeta/paideia/course-builder"><img src="https://agentmods.dev/badge/skills/optimeta/paideia/course-builder.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 | $0.00119 | $0.02584 |
| Opus 5 | $0.00060 | $0.01292 |
| Sonnet 5 | $0.00024 | $0.00517 |
| Haiku 4.5 | $0.00012 | $0.00258 |
Grade A, and why
course-builder 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 3d 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 — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Course Builder
Overview
This skill turns raw course materials into a structured knowledge base that downstream drilling commands (/twin, /blind, /chain, /pattern, /hwmap) can query. It is domain-general — the same pipeline works for a Linear Algebra course as for a Quantum Mechanics course.
Two-phase pipeline:
Phase 1: /ingest
materials/**/*.pdf → converted/**/*.md (via pdf skill)
materials/**/*.md → (copied as-is)
Phase 2: /analyze
converted/** + materials/*.md → course-index/patterns.md
course-index/coverage.md
course-index/summary.md
When to load
- User runs
/ingestor/analyze - User mentions adding new course materials
- User asks "what does this course cover" or "what are the key techniques"
- Downstream commands (
/twin,/blind,/pattern,/hwmap) needcourse-index/data that doesn't exist yet
Phase 1: Ingest
Discovery
Scan materials/ recursively. Classify each file by path and extension:
materials/lectures/*.pdf|.md— lecture notesmaterials/textbook/*.pdf|.md— textbook chaptersmaterials/homework/*.pdf|.md— HW problem sets (rename for consistency:hw1.pdf,hw2.pdf, ...)materials/solutions/*.pdf|.md— HW solutions (hw1_sol.pdf, etc.) or worked examples
Ambiguous location (e.g., a PDF in materials/ root)? Ask user once to categorize, then remember.
Conversion
All .pdf files in materials/** go through the vision pipeline. pdfplumber was tried as a fast path and proved unreliable on course materials — even prose-heavy textbook pages silently word-salad when they mix equations or multi-column figures. Routing everything uniformly through vision is simpler than maintaining per-category heuristics with fallbacks. Full pipeline in skills/pdf/VISION.md; the short form:
- Load
skills/pdf/SKILL.mdandskills/pdf/VISION.md. - Render each PDF to PNG at
dpi=160(viapdf2image) intoconverted/<category>/_pages/<stem>/. - Resize all rendered PNGs to ≤1800 px on the long edge before any agent starts reading — this is the hard 2000 px many-image limit; violating it wastes entire agent runs.
- Spawn one parallel
general-purposeagent per PDF. Each agent reads its own pages sequentially (not in parallel batches — same dimension limit) and transcribes to clean LaTeX markdown ($...$/$$...$$). Unreadable symbols get[?]. - Write
converted/<category>/<stem>.mdwith provenance:<!-- SOURCE: materials/<category>/<stem>.pdf, extracted <YYYY-MM-DD>, method: vision -->. - After all agents finish, delete the
_pages/scratch dirs.
What ships with it
1 file 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.
- 3d ago First seen · 198 lines · 119 tokens per session scan A dd81595a6945
course-builder is a skill published in the GitHub repository OPTIMETA/PAIDEIA (91 stars, last pushed 1mo ago), licensed MIT. It adds 119 tokens to every session and 2,584 once invoked, about $0.0006 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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