pm-os-onboarding
Skill3 starsChanged 22 days agoMITView on GitHub
Interactive setup for PM-Operating-System in Codex. Use when the user says onboard, PM-OS setup, set up PM-OS, or asks to configure this repo for Codex or dual-runtime.
In this repository24 other files it gives its agents.
- AGENTS.mdAGENTS.md
- docs/agents.mdAGENTS.md
- company-product-signalsSkill
- company-researcherSkill
- company-strategySkill
- brainstormingSkill
- continual-learningSkill
- decision-loggerSkill
- eval-briefSkill
- exec-communicatorSkill
- experiment-designerSkill
- experiment-writeupSkill
- knowledge-updaterSkill
- launch-postSkill
- launch-readinessSkill
- meeting-to-actionsSkill
- one-pagerSkill
- pptx-creatorSkill
- prd-writerSkill
- stakeholder-updateSkill
- strategy-connectorSkill
- what-ifSkill
- working-backwardsSkill
- writing-clearlySkill
The file
We split this skill into the rules it gives an agent
5 rules. About 0 are common, 3 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 21
Ask in small batches: company + role.
- Distinctive: line 22
After company + role, offer a short public-web research pass.
- Very specific: line 23
Write config/pm-os-config.yaml with runtime.primary and runtime.codex_install_scope.
- Distinctive: line 25
Run from repo root:
- Distinctive: line 31
Keep the conversation short.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
PM-OS Onboarding
Collect PM context, write config/pm-os-config.yaml, create a product dossier, run setup.
When to use
- onboard
- PM-OS setup
- set up PM-OS
- configure this repo
Workflow
- Confirm you will write config, copy
knowledge/products/_template/to a named product folder, and run./scripts/setup.sh. - Runtime: default
codex. Offerbothif they still use Cursor. Codex scope:repooruser. - Ask in small batches: company + role; product name + type; manager/VIPs; goals + deprioritize; Slack/Drive/GitHub/Figma/Jira/browser; MCP now or skip.
- After company + role, offer a short public-web research pass. Skip unless they want it.
- Write
config/pm-os-config.yamlwithruntime.primaryandruntime.codex_install_scope. Keep template booleans unless they opted out. Setskills.eval_brief: true. - Copy
knowledge/products/_template/→knowledge/products/<slug>/if that folder does not exist. - Run from repo root:
- Codex:
./scripts/setup.sh --runtime codex --codex-scope <repo|user> - Dual:
./scripts/setup.sh --runtime both --codex-scope <repo|user> - Cursor only if they asked:
./scripts/setup.sh --runtime cursor
- Codex:
- Next steps: fill
brief.md, thenevals.mdif the product is AI; example atknowledge/products/harbor-copilot/; Codex context inPM-OS-AGENTS.md; MCP in.codex/config.toml.continual-learningis Cursor-first.
Keep the conversation short. Do not invent company facts. Do not depend on Cursor-only tools.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

