alt

A command that imports an Exam Radar export and adds lecture-emphasis signals to a course index. Exam Radar is a study tool that ranks topics by how strongly a professor emphasized them in recordings.

In plain words
What is it for?
Use it to update radar.md, add lecture-emphasis information to coverage.md, and produce a weak-topic map for exam preparation.
Why use it?
It combines spoken lecture emphasis with homework coverage, giving the course index another signal for judging likely exam topics.

Command

Install

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.

agentmods
npx agentmods add commands/optimeta/paideia/alt
Clone the repo
git clone --depth 1 https://github.com/OPTIMETA/PAIDEIA
Per session 44 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,335 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00044 $0.01335
Opus 5 $0.00022 $0.00668
Sonnet 5 $0.00009 $0.00267
Haiku 4.5 $0.00004 $0.00134

Measured 2d ago against content hash fb17b7b355d8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

alt 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 2d 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.

plugins/paideia/commands/alt.md · 83 lines

How it starts

The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Output language

Read INTERFACE_LANG from .course-meta (default en). All user-facing prose — chat output and the narrative parts of generated MDs — must be in that language. Keep in English regardless: file paths, slash command names, the <!-- exam-radar:v1 ... --> marker, table column headers (Topic, Exam prob, Zone, Lecture emphasis, §, Title, HW coverage, Exam tier), tier markers (🔥🔥/🔥/🟡/⚪), the 🎙 signal flag, pattern IDs (P1..Pk), and § / Ch anchors — downstream tools (weakmap, hwmap, analyze) regex on them.

Load skills/alt-import/SKILL.md and skills/course-builder/SKILL.md (the latter for the coverage.md schema you will annotate).

Arguments (the pasted Exam Radar export, may be multi-line): $ARGUMENTS

What this is

Exam Radar is OPTIMETA's Alt plugin. It reads your lecture recordings and ranks topics by how much the professor emphasized them out loud — a second signal of exam probability, independent of PAIDEIA's HW density. Its 학습 로드맵 → 복사 button emits a fixed markdown form. This command folds that signal into course-index/.

HW density stays the primary exam-tier signal. Lecture emphasis is layered on as a second opinion: it corroborates where the two agree and flags blind spots where they diverge. It never silently rewrites the HW-based tier.

Step 0 — Get the export

  1. If $ARGUMENTS contains the export (look for <!-- exam-radar:v1), use it.
  2. Else if materials/radar.md exists, read that.
  3. Else: tell the user (in $INTERFACE_LANG) and stop:
    • en: "In Exam Radar, use 학습 로드맵 → 복사 (Study roadmap → Copy), then paste it after /paideia:alt — or save it as materials/radar.md."
    • ko: "Exam Radar에서 학습 로드맵 → 복사/paideia:alt 뒤에 붙여넣거나, materials/radar.md로 저장하세요."
  4. Validate the marker. No <!-- exam-radar:v1 → not an Exam Radar export; stop. Version > 1 → warn that this command parses v1 and may ignore new fields, then proceed best-effort.

Pipeline

Follow skills/alt-import/SKILL.md end to end:

Read the full file on GitHub · 83 lines

Changes

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.

  1. 2d ago First seen · 83 lines · 44 tokens per session scan A fb17b7b355d8

Subscribe to this mod's changes

alt is a command published in the GitHub repository OPTIMETA/PAIDEIA (91 stars, last pushed 1mo ago), licensed MIT. It adds 44 tokens to every session and 1,335 once invoked, about $0.0002 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.