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 mehdiforoozandeh/crux --skill prezitgit clone --depth 1 https://github.com/mehdiforoozandeh/cruxWrote 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/mehdiforoozandeh/crux/prezit)<a href="https://agentmods.dev/skills/mehdiforoozandeh/crux/prezit"><img src="https://agentmods.dev/badge/skills/mehdiforoozandeh/crux/prezit/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/mehdiforoozandeh/crux/prezit"><img src="https://agentmods.dev/badge/skills/mehdiforoozandeh/crux/prezit.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 | $0.00200 | $0.02779 |
| Opus 5.5 | $0.00080 | $0.01112 |
| Sonnet 5.5 | $0.00040 | $0.00556 |
| Haiku 4.5 | $0.00020 | $0.00278 |
Grade A, and why
prezit 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.
How it starts
The opening of the file, as written. The whole thing — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
prezit — presentations from a subtree
One anchor, one story. The body of the deck is the anchor and everything under it; the intro is built from the anchor's ancestors and the wiki pages they link. A hypothesis anchor is legal and yields a shorter deck. No time-window, no multi-anchor: "what happened this week" is answered by choosing the anchor whose subtree moved.
The three-way split (who does what)
| part | who | what |
|---|---|---|
crux deck <anchor> --json |
engine | the entire story material, assembled deterministically |
assets/deck.html, examples/paper_deck/ |
this skill's template and paper-arc build | all chrome: palette, fade, keyboard nav, progress, DOM-derived count, speaker notes |
| the deck's prose + charts | you, the agent | narrative selection, the hero figures, the bullets |
crux deck --verify/--refresh/--lint |
engine | proves numbers and sources match; repairs addressed values; checks the slide contract |
You never retype the chrome (copy the template), and you never let the engine author a sentence — selection and phrasing are your whole job.
Two arcs — the paper arc is the default
| arc | shape | numbers proved by | start from |
|---|---|---|---|
| paper arc (default) | motivation → method → results → discussion | build_deck.py embeds result files as DATA and records each file's sha256; --verify re-reads them |
examples/paper_deck/ |
| tree arc (the PI picks it) | title → lineage → question → method → results → verdict, built from the tree as mapped below | metrics.json addresses, each checked by --verify |
assets/deck.html, examples/q1_scaling_deck.html |
For the paper arc, read references/paper-arc.md before
drafting: its slide roles, style rules and build replace the tree-arc defaults below (the
mapping, numbers by role, no future-work slide). Everything else in this file applies to
both arcs.
The mapping — what each crux object becomes (tree arc)
What ships with it
6 files 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.
- 2d ago Changed · +29 lines · +39 tokens per session a01ed6f722d5
- 1mo ago First seen · 155 lines · 161 tokens per session scan A 5e32247d3940
prezit is a skill published in the GitHub repository mehdiforoozandeh/crux (18 stars, last pushed today), licensed MIT. It adds 200 tokens to every session and 2,779 once invoked, about $0.0008 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 2026-08-31.
Other skills, from other repositories
ab-testing
Use when designing or analyzing a controlled experiment — falsifiable hypothesis, sample size from an MDE, reading significance/CI/power, CUPED, or rescuing tests that won't go significant. NOT recurring metric tracking (that is analytics), NOT north-star/KPI trees (that is kpi-framework), NOT projecting metrics…
research-manager
Use this when starting a new research project or managing a complex, multi-step research workflow.
academic-writing
You must use this when producing any research prose — literature reviews, syntheses, analyses, methodology descriptions, discussion sections, abstracts, or any written output intended for an academic audience.
ab-testing-ecommerce
Run controlled experiments on product pages, checkout flows, and pricing to find what converts best using statistical significance testing.
systematic-review
You must use this when conducting PRISMA-standard systematic reviews, protocol development, or Risk of Bias assessment.
hypothesis-testing
You must use this when formulating testable hypotheses, designing experimental controls, or defining falsification criteria.