Agent skill · Workflow & Productivity

huge-plan

Use huge-plan for open-ended high-risk repo efforts needing websearch during brainstorming and refinement until convergence; exclude direct implementation-only, factual/explanation, trivial, or explicit no-plan requests.

Optim-Agentgithub.com/Optim-AgentGitHub ↗
claude-codecodexMIT
Install
npx skills add Optim-Agent/optim-plans --skill huge-plan --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 1 KB
Bundled scripts: none
Path: skills/huge-plan/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 288
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Huge Plan Read and follow `../optim-plans/SKILL.md`, treating the request as if it named `huge-plan`. Depth: `huge-plan` means at least 10 planning questions, no planning-question maximum, required websearch during brainstorming and refinement, no refinement round or timeout limit, and at most five high-priority comments or questions per round.

More from optim-plans
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About this skill
What does the huge-plan skill do?

Use huge-plan for open-ended high-risk repo efforts needing websearch during brainstorming and refinement until convergence; exclude direct implementation-only, factual/explanation, trivial, or explicit no-plan requests.

How do I install it?

Run `npx skills add Optim-Agent/optim-plans --skill huge-plan --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From Optim-Agent/optim-plans, a repository with 288 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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