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 Canvas-LMS-MCP/canvas-teacher-mcp --skill slide-plangit clone --depth 1 https://github.com/Canvas-LMS-MCP/canvas-teacher-mcpWrote 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/canvas-lms-mcp/canvas-teacher-mcp/slide-plan)<a href="https://agentmods.dev/skills/canvas-lms-mcp/canvas-teacher-mcp/slide-plan"><img src="https://agentmods.dev/badge/skills/canvas-lms-mcp/canvas-teacher-mcp/slide-plan/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/canvas-lms-mcp/canvas-teacher-mcp/slide-plan"><img src="https://agentmods.dev/badge/skills/canvas-lms-mcp/canvas-teacher-mcp/slide-plan.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 | $0.00107 | $0.00603 |
| Opus 5 | $0.00053 | $0.00302 |
| Sonnet 5 | $0.00021 | $0.00121 |
| Haiku 4.5 | $0.00011 | $0.00060 |
Grade A, and why
slide-plan 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.
What it actually says
slide-plan — per-slide section blocks (Skill 2)
Sub-skill of module-overview-page (Skill 1). When a module has multiple slide decks, each
slide reads best as its own section: what the slide covers + the assignments/labs based on it,
with that slide embedded right there.
Model
from slide_plan import slide_sections
sections = slide_sections([
{"title": "📽️ Slide 1 — While Loops",
"summary_html": "<p>Covers the while-loop pattern: condition, update, sentinel stop.</p>",
"tasks": [("assignment", 1314443, "Assignment 5-0 — Power Number"),
("assignment", 1314445, "Assignment 5-1 — Input Validation")],
"deck_id": "<SLIDE_1_DECK_ID>"},
{"title": "📽️ Slide 2 — For Loops", "summary_html": "<p>…</p>",
"tasks": [("assignment", 1314447, "Assignment 5-3 — Count Random")],
"deck_id": "<SLIDE_2_DECK_ID>"},
])
# then hand `sections` to Skill 1:
# make_page(course_slug, slug, overview_html, sections, deck_id=None, ...)
Each dict → a (header, summary_html, tasks, deck_id) section. tasks items = (kind, ref, label)
(kind ∈ assignment/page/quiz/url/text) — the SAME item shape Skill 1 renders.
What is AUTHORED vs CANON
- Authored (the AI): each slide's
title,summary_html(read the real deck to summarize it — concrete, NO<code>), and whichtasksderive from it. - Canon: the packing (
slide_plan.py) + the rendering/embedding (Skill 1'smodule_overview.py).
How it fits
Skill 1 (module-overview-page) drives the page; for a multi-slide module it calls this to produce the
sections. A single-slide module doesn't need this — Skill 1 uses a page-level deck_id + plain
category sections instead.
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 · 41 lines · 107 tokens per session scan A 6892a2d8852d
slide-plan is a skill published in the GitHub repository Canvas-LMS-MCP/canvas-teacher-mcp (1 stars, last pushed 27d ago), licensed MIT. It adds 107 tokens to every session and 603 once invoked, about $0.0005 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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