promptlisted

Analyze one or more GitHub issues, classify complexity, and produce a copy-paste-ready prompt with a model recommendation. The goal is quality-conservative right-sizing — never under-resource a task, but don't waste Opus tokens on a typo fix. ## Model Lineup & Effort Levels The fleet is **Fable, Opus, Sonnet, Haiku** — the same four families named in `CLAUDE.md`, `.claude/rules/subagent-orchestration.md` "Model Selection", and `.claude/agents/README.md`. In the Claude Code picker, **Opus** is the default. **Always name the family, never the version** (#791). A bare family name means the current non-legacy model of that family, so it never goes stale — earlier generations still listed in the picker are Legacy and are never recommended. The bare aliases used elsewhere (agent frontmatter, spawn sites) resolve the same way: `opus`, `sonnet`, `haiku`, and `fable` each resolve to the newest non-legacy model of that family. Write an explicit model ID (e.g. `claude-opus-5`) **only** where a tool literally consumes the string. Full rule and its scope: `.claude/agents/README.md` "Model naming". The picker's second control is **effort**, and this skill recommends one on every issue. Use the picker's own labels — **Low**, **Medium**, **High**, **Extra**, **Max** — because a recommendation the user cannot map onto the control in front of them is one they ignore. This is the **one place** the label↔token mapping is taught, for the cases where something downstream consumes the raw token