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/ai-swiss/base/preparer-sequencenpx skills add ai-swiss/base --skill preparer-sequencegit clone --depth 1 https://github.com/ai-swiss/baseWrote 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/ai-swiss/base/preparer-sequence)<a href="https://agentmods.dev/skills/ai-swiss/base/preparer-sequence"><img src="https://agentmods.dev/badge/skills/ai-swiss/base/preparer-sequence.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 | $0.00028 | $0.01464 |
| Opus 5 | $0.00014 | $0.00732 |
| Sonnet 5 | $0.00006 | $0.00293 |
| Haiku 4.5 | $0.00003 | $0.00146 |
Grade A, and why
preparer-sequence 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 4d 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 — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Préparer une séquence
Préparer une séquence d'enseignement de bout en bout: objectifs d'apprentissage, prérequis, déroulé par phases, différenciation, matériel. La séquence est un document de travail pour l'enseignant, non un script à suivre mot à mot.
Inputs
Demande à l'utilisateur:
- Le sujet: quelle notion, quel thème?
- La classe concernée: pour lire son profil dans
classes/ - La durée: combien de périodes, sur combien de semaines?
Avant de commencer, vérifie que profil/enseignant.md est rempli: sinon, charge skills/processes/configuration/SKILL.md.
Lis la compétence skills/competences/metier-enseignement/SKILL.md pour l'alignement pédagogique et la formulation des objectifs.
Si .ai/journal/ contient des entrées récentes, lis-les pour le contexte.
Étapes
1. Comprendre le besoin
«Si je comprends bien, vous préparez [sujet] pour la classe [identifiant], sur [durée]. Quelques questions pour bien cerner le besoin:»
Questions à poser une par une:
- Où cette séquence s'inscrit-elle dans votre programme annuel?
- Qu'est-ce que les élèves savent déjà sur ce sujet?
- Y a-t-il un passage du plan d'études que vous visez en particulier?
← Reformulation
2. Objectifs d'apprentissage
Propose 2 à 4 objectifs observables, formulés avec des verbes d'action (voir la taxonomie dans la compétence métier):
«Voici les objectifs que je propose. À la fin de la séquence, les élèves seront capables de:
- [objectif avec verbe d'action observable]
- [objectif]
Est-ce que cela correspond à ce que vous visez? Faut-il en ajouter, en retirer, ou viser plus haut ou plus bas?»
← Reformulation
3. Prérequis
Liste ce que les élèves doivent déjà maîtriser pour aborder la séquence. Croise avec le profil de classe:
«Pour ces objectifs, les prérequis sont: [liste]. D'après le profil de votre classe, [point d'attention éventuel]. Prévoyons-nous un rappel en début de séquence?»
← Reformulation
4. Déroulé par phases
Construis le déroulé période par période, en phases courtes:
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.
- 4d ago First seen · 134 lines · 28 tokens per session scan A 7d2a7cf0c3d3
preparer-sequence is a skill published in the GitHub repository ai-swiss/base (42 stars, last pushed today), licensed Apache-2.0. It adds 28 tokens to every session and 1,464 once invoked, about $0.0001 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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