According to AlphaMoat, as of 2026-10, Using Superpowers has 54,155 downloads and 79 stars — ranked by downloads #460 among 10,914 AI skills in this ranking, and #96 of 1,632 in AI Agent.
The list defaults to total downloads and can also be sorted by stars; detail-page rankings use total downloads.
| Platform | Downloads | Stars | Comments |
|---|---|---|---|
| ClawHub ↗ | 36.3K | 63 | - |
| SkillHub ↗ | 54.2K | 79 | — |
Platforms count differently and update at different times.
The source gives one rule: before any response or clarifying question, check whether a relevant skill exists, invoke it when there is a chance it applies, and drop it if it turns out wrong. A flow diagram fixes the order. On each message, decide whether a skill might apply, invoke it and state what it is being used for, create a todo per item when the skill carries a checklist, then follow the skill exactly, and answer directly only when nothing applies. A table of red flags lists the usual excuses, such as calling something a simple question, exploring the code first, or trusting memory of a skill, and rejects each. When several skills could apply, process skills such as brainstorming or debugging come before implementation skills, rigid skills are followed as written, and flexible ones are adapted. Loading uses the Skill tool the host provides, the source names Claude Code, and other environments are told to check their own documentation.
Profile published 2026-10-26
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change. Other skills share this name; figures from before the change are attributed to this one, which currently has the most downloads.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-10 | 54.2K | — | 79 |
| 2026-09 | 39.3K | — | 79 |
| 2026-08 | 35.8K | +1.4% | 79 |
| 2026-07 | 35.3K | — | 79 |
| 2026-05 | 32.0K | — | 69 |
| 2026-03 | 23.1K | — | 49 |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
--- name: using-superpowers description: Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions --- <EXTREMELY-IMPORTANT> If you think there is even a 1% chance a skill might apply to what you are doing, you ABSOLUTELY MUST invoke the skill. IF A SKILL APPLIES TO YOUR TASK, YOU DO NOT HAVE A CHOICE. YOU MUST USE IT.
This is not negotiable. This is not optional. You cannot rationalize your way out of this.
</EXTREMELY-IMPORTANT>
## How to Access Skills
**In Claude Code:** Use the `Skill` tool. When you invoke a skill, its content is loaded and presented to you—follow it directly. Never use the Read tool on skill files.
**In other environments:** Check your platform's documentation for how skills are loaded.
# Using Skills
## The Rule
**Invoke relevant or requested skills BEFORE any response or action.** Even a 1% chance a skill might apply means that you should invoke the skill to check. If an invoked skill turns out to be wrong for the situation, you don't need to use it.
```dot
digraph skill_flow {
"User message received" [shape=doublecircle];
"Might any skill apply?" [shape=diamond];
"Invoke Skill tool" [shape=box];
"Announce: 'Using [skill] to [purpose]'" [shape=box];
"Has checklist?" [shape=diamond];
"Create TodoWrite todo per item" [shape=box];
"Follow skill exactly" [shape=box];
"Respond (including clarifications)" [shape=doublecircle];
"User message received" -> "Might any skill apply?";
"Might any skill apply?" -> "Invoke Skill tool" [label="yes, even 1%"];
"Might any skill apply?" -> "Respond (including clarifications)" [label="definitely not"];
"Invoke Skill tool" -> "Announce: 'Using [skill] to [purpose]'";
"Announce: 'Using [skill] to [purpose]'" -> "Has checklist?";
"Has checklist?" -> "Create TodoWrite todo per item" [label="yes"];
"Has checklist?" -> "Follow skill exactly" [label="no"];
"Create TodoWrite todo per item" -> "Follow skill exactly";
}
```
## Red Flags
These thoughts mean STOP—you're rationalizing:
| Thought | Reality |
|---------|---------|
| "This is just a simple question" | Questions are tasks. Check for skills. |
| "I need more context first" | Skill check comes BEFORE clarifying questions. |
| "Let me explore the codebase first" | Skills tell you HOW to explore. Check first. |
| "I can check git/files quickly" | Files lack conversation context. Check for skills. |
| "Let me gather information first" | Skills tell you HOW to gather information. |
| "This doesn't need a formal skill" | If a skill exists, use it. |
| "I remember this skill" | Skills evolve. Read current version. |
| "This doesn't count as a task" | Action = task. Check for skills. |
| "The skill is overkill" | Simple things become complex. Use it. |
| "I'll just do this one thing first" | Check BEFORE doing anything. |
| "This feels productive" | Undisciplined action wastes time. Skills prevent this. |
| "I know what that means" | Knowing the concept ≠ using the skill. Invoke it. |
## Skill Priority
When multiple skills could apply, use this order:
1. **Process skills first** (brainstorming, debugging) - these determine HOW to approach the task
2. **Implementation skills second** (frontend-design, mcp-builder) - these guide execution
"Let's build X" → brainstorming first, then implementation skills.
"Fix this bug" → debugging first, then domain-specific skills.
## Skill Types
**Rigid** (TDD, debugging): Follow exactly. Don't adapt away discipline.
**Flexible** (patterns): Adapt principles to context.
The skill itself tells you which.
## User Instructions
Instructions say WHAT, not HOW. "Add X" or "Fix Y" doesn't mean skip workflows.
Records learnings, errors and corrections as Markdown files for later reuse and promotion into workspace memory.
Finds skills in local and remote catalogs from a plain-language request and recommends what to install.
A browser-automation command line skill for AI agents.
Turns corrections and self-review into tiered memory and promotes or archives it by use.
A workspace setup guide for planning proactive follow-up, working memory and review routines for an AI agent.
A guide to creating and updating effective Claude skills.
Reviews a third-party skill's source, permissions, and danger patterns against a checklist before it is installed.
以李白(701—762,字太白,号青莲居士,世称诗仙)的诗学观、意象系统与口吻,进行唐诗赏析、文学评论、考据问答与拟体创作。触发词:李白、李太白、太白、青莲居士、诗仙、谪仙人、将进酒、静夜思、蜀道难、唐诗、盛唐诗人、浪漫主义诗人、拟李白风格、以李白视角、李白会怎么写、用李白口吻。能力:诗词鉴赏与风格DNA解析、诗学观与文学谱系评述、诗句出处考据与真伪边界标注、以李白口吻答问、拟李白体旧体诗(必显式标注非原作)。适用边界:仅用于唐代文学与古典诗歌相关话题,非此类话题不触发;本 skill 为文学普及与研究辅助,不代表李白本人立场,所拟之作均非李白原作;涉及生平佚事、篇目归属等内容不构成学术定论,皆标存疑或待考。
A skill that turns an idea into a design and spec before any implementation.
writing-plans turns requirements into a detailed implementation plan before coding.
Dispatches a fresh subagent per task to execute an implementation plan in this session.
Run appropriate checks and inspect results before claiming work is complete, fixed, or passing.
Requesting Code Review helps verify work against requirements after tasks, major features, or before merging.
Data as of 2026-10. Downloads and stars are aggregated monthly from public skill registries (ClawHub, SkillHub). See data methodology.