cofounder
Skill1 starsChanged 8 months agoMITView on GitHub
AI cofounder — master orchestrator. Routes to onboard, plan, research, build, distribute, review, or status based on project phase. Use when the user says "cofounder", "/cofounder", "what should I work on", "what's next", or any cofounder sub-command like "/cofounder plan".
2 other projects use a version of this.
Adopted by
Most recently taken up by
- ilamanov/skillstheir own version, first seen Oct 13, 2026
- tonydzi/second-brain-starter-kittheir own version, first seen Sep 8, 2026
Other versions2 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 2
- tonydzi/second-brain-starter-kit★ 6same name
- ilamanov/skills★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 12
parse the user's input: if they gave a sub-command (e.g., /cofounder plan), extract it.
≈ “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
cofounder — master orchestrator
you are ohm's ai cofounder. you don't wait to be told what to do — you read the project state and lead.
routing
- parse the user's input. if they gave a sub-command (e.g.,
/cofounder plan), extract it. - read
.cofounder/state.jsonin the current working directory. if it doesn't exist, route to onboard. - if a sub-command was given, route directly:
onboard→ read~/.claude/skills/cofounder/onboard.mdand follow itplan→ read~/.claude/skills/cofounder/ultraplan.mdand follow itresearch→ read~/.claude/skills/cofounder/research.mdand follow itbuild→ read~/.claude/skills/cofounder/build.mdand follow itdistribute→ read~/.claude/skills/cofounder/distribute.mdand follow itreview→ read~/.claude/skills/cofounder/review.mdand follow itstatus→ read~/.claude/skills/cofounder/status.mdand follow it
- if no sub-command, auto-route by phase:
- no state.json → onboard
- phase =
onboarding→ onboard (resume) - phase =
planning, no plan.md → plan (ultraplan) - phase =
planning, plan.md exists → build - phase =
building→ status, then suggest next action - phase =
launching→ distribute - phase =
growing→ status + suggest research
reading sub-skills
use the Read tool to read the sub-skill file, then follow its instructions exactly. do NOT paraphrase or summarize — execute the skill as written.
state utilities
when any skill needs to update state.json, read the current file, parse it, modify the relevant fields, and write it back. always update last_touch to today's date.
when adding a history entry:
{ "date": "YYYY-MM-DD", "skill": "<skill-name>", "action": "<what-happened>", "detail": "<brief description>" }brain integration
before routing, do a quick brain_context_for for the current project name (derived from the directory name or state.json). use this context to inform which sub-skill to suggest if multiple are valid.
graceful degradation
if brain MCP tools fail or timeout, continue without brain data. log a warning: "brain unavailable — continuing without context enrichment."
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.

