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 causify-ai/helpers --skill slides.add_tutorial_linksgit clone --depth 1 https://github.com/causify-ai/helpersWrote 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/causify-ai/helpers/slides.add_tutorial_links)<a href="https://agentmods.dev/skills/causify-ai/helpers/slides.add_tutorial_links"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/slides.add_tutorial_links/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/causify-ai/helpers/slides.add_tutorial_links"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/slides.add_tutorial_links.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 3 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
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 | $0.00011 | $0.00463 |
| Opus 5.5 | $0.00004 | $0.00185 |
| Sonnet 5.5 | $0.00002 | $0.00093 |
| Haiku 4.5 | $0.00001 | $0.00046 |
Grade A, and why
slides.add_tutorial_links 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 1mo 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
Goal
-
Given a slides file
<SMD_FILE>and a rendered HTML tutorial<TUTORIAL_URL>, add links from each slide to the tutorial section it corresponds to- E.g.,
<SMD_FILE>=msml610/lectures_source/Lesson09.3-Multi_Armed_Bandits.txtand<TUTORIAL_URL>=https://raw.githack.com/gpsaggese/gpsaggese.github.io/gp_scratch/msml610/tutorials/L09_multi_armed_bandits/L09_03_02_multi_armed_bandits.html
- E.g.,
Workflow
Find the Relationship
- Read
<SMD_FILE>and<TUTORIAL_URL> - If a companion tutorial markdown file exists next to the notebook (e.g.,
<TUTORIAL_DIR>/<TUTORIAL_NAME>.md), use it to help match slide content to tutorial cells - Match each slide to the tutorial cell(s) that cover the same concept
Add Links
- For each match, add a link in the slide to the tutorial anchor for that
cell
- The anchor is the rendered HTML's cell heading, e.g.
<TUTORIAL_URL>#Cell-1:-Introduction---Casino-Slot-Machines
- The anchor is the rendered HTML's cell heading, e.g.
- Do not add a link when no tutorial cell clearly corresponds to the slide
Leave Structure and Content Unchanged
- Do not change the structure of the text (titles, bullet hierarchy, div fenced blocks) or the substantive content: add only the link
Conventions
- Follow the role specified in
.claude/skills/role.ai_researcher.md - Follow the conventions in
.claude/skills/slides.rules.md
Verification
- Check that each added anchor points to an actual heading in
<TUTORIAL_URL>, not a guessed slug - Make sure that the updated slides render correctly, e.g.,
> gen_slides.py -i <FILE> --notes_to_pdf_args="--skip_action open_pdf"
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.
- 1mo ago Changed · +5 lines · -3 tokens per session c3ae32571b7a
- 1mo ago First seen · 41 lines · 14 tokens per session scan A bca2c9ba00a4
slides.add_tutorial_links is a skill published in the GitHub repository causify-ai/helpers (150 stars, last pushed yesterday), licensed Apache-2.0. It adds 11 tokens to every session and 463 once invoked, about $0.0000 per session on Opus 5.5. 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 2026-09-03.
Other skills, from other repositories
hr-onboarding
A new-hire onboarding plan as a single page — first week schedule, buddy + manager intro, learning track, equipment checklist, and "you're set when…" outcomes. Use when the brief mentions "onboarding", "new hire", "first week plan", or "入职".
book-mirror
Take any book (EPUB/PDF), produce a personalized chapter-by-chapter analysis. Each chapter is preserved in detail (The Chapter) and mirrored back to the reader's actual life (The Mirror) using brain context. The mirror observes and resonates — a friend pointing out parallels, NOT a consultant rearranging the reader's…
exam-forecast
Analyze past exams from the same professor to surface patterns — subject weighting, recurring issue-spot traps, favored hypo types, policy-vs-doctrine mix — and forecast likely emphases for the upcoming exam. Use when the user says "what's on the exam", "analyze past exams", "predict the exam", or shares past exams.
lean-formalize
Develop and verify a mathematical proof in Lean, continue an incomplete Lean project, or audit whether it proves the original statement. Connect actual inputs to intermediate lemmas, assemble the target theorem, check its transitive axioms, and provide a reproducible handoff. Use when Lean is requested or a specific…
miniapp
Build a tiny interactive HTML playground only when someone asks to see, play with, or step through a mechanism.
eli5
Explain research, papers, or technical ideas in plain English with minimal jargon, concrete analogies, and clear takeaways. Use when the user says "ELI5 this", asks for a simple explanation of a paper or research result, wants jargon removed, or asks what something technically dense actually means.