Borrowing it
Nothing to install: this file belongs to zhouguoqing/QianYuan.AIAgenticFramework. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/zhouguoqing/QianYuan.AIAgenticFramework/main/.agents/skills/using-superpowers/SKILL.mdgit clone --depth 1 https://github.com/zhouguoqing/QianYuan.AIAgenticFrameworkWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/zhouguoqing/qianyuan.aiagenticframework/using-superpowers)<a href="https://agentmods.dev/skills/zhouguoqing/qianyuan.aiagenticframework/using-superpowers"><img src="https://agentmods.dev/badge/skills/zhouguoqing/qianyuan.aiagenticframework/using-superpowers/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/zhouguoqing/qianyuan.aiagenticframework/using-superpowers"><img src="https://agentmods.dev/badge/skills/zhouguoqing/qianyuan.aiagenticframework/using-superpowers.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00026 | $0.00443 |
| Opus 5.5 | $0.00010 | $0.00177 |
| Sonnet 5.5 | $0.00005 | $0.00089 |
| Haiku 4.5 | $0.00003 | $0.00044 |
Grade A, and why
using-superpowers scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Using Superpowers
The Core Rule
If there is even a 1% chance a skill applies to the current task, invoke it.
Skills are cheap to load. Failing to use an applicable skill is expensive.
How to Find Skills
At the start of every new task:
- Review available skills (check
~/.openclaw/extensions/superpowers/skills/) - Ask: "Does any skill match what I'm about to do?"
- If yes → load and follow the skill exactly
- If no → proceed with default behavior
In OpenClaw's persistent agent context, check skills at the start of every new task, not just new conversations. A long-running session may handle many different task types.
Decision Flowchart
New task received
↓
Does any skill apply? (even 1% chance → YES)
↓
YES → Announce: "Using [skill-name] to [purpose]"
Load skill file
Follow instructions exactly
↓
Complete or hand off cleanly
NO → Proceed with default agent behavior
Priority Hierarchy
- User instructions — always highest priority
- Skills — override default behavior when applicable
- Default behavior — fallback when no skill applies
Announcing Skill Usage
When you invoke a skill, say so:
"Using
brainstormingto explore approaches before writing code." "Usingsystematic-debuggingto diagnose this error."
This keeps the human informed and lets them redirect if needed.
OpenClaw-Specific Notes
- In persistent sessions, skills should be checked at the start of each new task, not just session start
- Skills around
task-handoffandagent-self-recoverymatter more in OpenClaw than in session-based tools — don't skip them - If a task will take more than ~20 minutes, check
long-running-task-managementfirst
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 61 lines · 26 tokens per session scan A 9ee65e60f9c2
using-superpowers is a skill published in the GitHub repository zhouguoqing/QianYuan.AIAgenticFramework (37 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 26 tokens to every session and 443 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
git-checkpoint
Use git as a safety net - create a checkpoint commit before risky or large changes and roll back cleanly if a change makes things worse. Use before multi-file refactors.
synthesize-report
Produces a citation-grounded summary across one or more workspace source files for summaries, briefings, literature reviews, or comparisons.
summarizer
Use when the user asks for a summary, TL;DR, or condensed version of any content.
craft-studio
Router for the ArtCraft craft apps (PhotoCraft, VectorCraft, FilmCraft, LightCraft, PdfCraft, EffectCraft, DesignCraft, FigCraft, WordCraft, SoundCraft, DeckCraft, CADCraft, GridCraft) driven headless via pi-craft. Use to choose which app fits a job and run the discover-execute-save-verify loop - "which craft app…
craft-video-post
Footage/Veo clips to a finished mp4 with ArtCraft apps - FilmCraft assembly and alpha overlays, SRT captions, SoundCraft mix, h264+aac delivery; verified and resumable. Use for "edit these clips into a finished video with captions and music", "add a lower third and subtitles to my footage", "post-produce this…
faq-mine
Mine docs/faq.md from README.md, docs/.md, and the pi-hermes memory stores. Dispatches @fast subagents per source, dedupes against the existing FAQ, and merges entries in caveman style. Use when asked to "build / regenerate / extend the FAQ", "mine docs into FAQ", "mine hermes memory into FAQ", "surface runtime…