onboarding-pm

onboarding-pm is a skill for Claude Code from Ludovic33Fr/product-ai-toolbox. It costs 60 tokens per session (1,650 once invoked), scanned A, original, MIT.

A French-language framework for onboarding a new product manager, the person responsible for deciding what a product should build and why. It creates a tailored learning path from the team’s documents, recent decisions, tensions, key contacts, and an introductory project.

In plain words
What is it for?
Use it to prepare first-week questions, priority meetings, context review, and an initial project for a newly hired or transferred product manager.
Why use it?
It helps a new product manager understand the team’s context and priorities without following a generic orientation plan. It adapts the onboarding to the person’s experience and responsibilities.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the pm-augmente plugin — 12 skills, 6 agents shipped together

Good fit Use it to prepare first-week questions, priority meetings, context review, and an initial project for a newly hired or transferred product manager.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ludovic33fr/product-ai-toolbox/onboarding-pm
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.

Any agent
npx skills add Ludovic33Fr/product-ai-toolbox --skill onboarding-pm
Clone the repo
git clone --depth 1 https://github.com/Ludovic33Fr/product-ai-toolbox

Made for: Claude Code.

Or install pm-augmente, the plugin that ships this one along with the rest of its 12 skills, 6 agents.

Wrote 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.

agentmods badge for onboarding-pm

README.md
[![agentmods](https://agentmods.dev/badge/skills/ludovic33fr/product-ai-toolbox/onboarding-pm/github.svg)](https://agentmods.dev/skills/ludovic33fr/product-ai-toolbox/onboarding-pm)
Your own site
<a href="https://agentmods.dev/skills/ludovic33fr/product-ai-toolbox/onboarding-pm"><img src="https://agentmods.dev/badge/skills/ludovic33fr/product-ai-toolbox/onboarding-pm/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.

agentmods 80×15 button for onboarding-pm

Your own site · 80×15
<a href="https://agentmods.dev/skills/ludovic33fr/product-ai-toolbox/onboarding-pm"><img src="https://agentmods.dev/badge/skills/ludovic33fr/product-ai-toolbox/onboarding-pm.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 60 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,650 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00060 $0.01650
Opus 5 $0.00030 $0.00825
Sonnet 5 $0.00012 $0.00330
Haiku 4.5 $0.00006 $0.00165

Measured 12d ago against content hash e5b5fb213e1d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

onboarding-pm 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.

skills/onboarding-pm/SKILL.md · 157 lines

How it starts

The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.

onboarding-pm

Fiche éditoriale

Objectif. Produire un parcours d'onboarding pour un nouveau PM rejoignant l'équipe.

Entrées. Profil du nouveau PM, périmètre, base documentaire accessible.

Sorties. Questions clés à poser à la base, décisions structurantes récentes, zones de tension, rencontres prioritaires, projet introductif.

Cadence d'usage. À chaque nouvelle arrivée.

Mode opératoire

Quand m'invoquer

Un nouveau PM arrive et l'utilisateur (manager ou pair) prépare son parcours d'onboarding. Il me fournit le profil du nouveau PM (séniorité, contexte précédent, forces, lacunes connues), le périmètre qu'il va prendre, et l'accès à la base documentaire produit.

Procédure

  1. Lire la base documentaire dans la limite de ce qui est accessible : roadmap actuelle, décisions récentes, journal de décision si disponible, notes de discovery, OKR.
  2. Adapter le parcours au profil : un PM senior n'a pas besoin du même onboarding qu'un PM junior. Calibrer les rencontres prioritaires, le projet introductif, et le niveau de détail.
  3. Produire les 8-12 questions-clés que le nouveau PM devrait poser à la base documentaire dans sa première semaine. Une bonne question est ouverte, factualisable, et révèle des zones d'ombre du périmètre.
  4. Lister les 5-8 décisions structurantes récentes (3-6 derniers mois) que le nouveau PM doit connaître pour comprendre le contexte. Pour chacune : la décision, son contexte, son statut actuel.
  5. Identifier les zones de tension : sujets en débat, dépendances tendues, équipes en désaccord, dette tech ou produit qui bloque. À traiter en lecture orale (au cours d'une 1:1), pas dans un doc public.
  6. Recommander 5-8 rencontres prioritaires : qui voir, dans quel ordre, sur quoi. Inclure systématiquement : un dev senior, un user / customer success, un stakeholder business.
  7. Définir un projet introductif : un sujet limité, livrable en 4-6 semaines, qui force le nouveau PM à toucher tous les segments du périmètre sans porter d'enjeu critique.
  8. Produire la sortie au format ci-dessous.

Read the full file on GitHub · 157 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. 12d ago First seen · 157 lines · 60 tokens per session scan A e5b5fb213e1d

Subscribe to this mod's changes

onboarding-pm is a skill published in the GitHub repository Ludovic33Fr/product-ai-toolbox (1 stars, last pushed 4mo ago), licensed MIT. It adds 60 tokens to every session and 1,650 once invoked, about $0.0003 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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