Using Superpowers

OpenAIOfficialCreated by Jesse VincentDistributed by OpenAI

Skill
Meta (authoring, orchestration, planning, memory)
Agent tooling
MIT
No issues found

From the author

Use when starting any conversation - establishes how to find and use skills, requiring skill invocation before ANY response including clarifying questions

— the description by Jesse Vincent

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The using-superpowers skill establishes a strict operational framework for AI agents. It mandates that agents must check for and invoke applicable skills before taking any action, including asking clarifying questions or performing initial research. By enforcing this discipline, the skill prevents agents from rationalizing away the use of structured processes, ensuring that tasks are handled consistently and according to established best practices.

What it does

Requires agents to evaluate skill applicability before any response or action.
Forces the invocation of relevant skills even for simple tasks or clarifying questions.
Prioritizes process skills (like brainstorming or debugging) over implementation skills.
Provides a list of red flags to help agents identify and stop rationalization behaviors.
Integrates with platform-specific reference files for tool mapping and environment handling.

When to use it

At the very beginning of every new conversation or task.
Before initiating any planning, research, or codebase exploration.
Whenever a user request could potentially be addressed by an existing skill.
When an agent feels tempted to skip a formal process for the sake of speed or simplicity.

Advantages

Ensures consistent application of best practices across all interactions.
Prevents undisciplined, ad-hoc actions that can lead to errors or wasted effort.
Maintains context and structure by forcing agents to follow defined workflows.
Reduces the likelihood of agents ignoring established protocols through rationalization.

Usage examples

“Can you help me fix this bug in the login module?”: The agent identifies the relevant debugging skill, announces 'Using systematic-debugging to fix the login bug', and initiates the debugging workflow before attempting any code changes.
“What do you think about this new feature idea?”: The agent recognizes the need for structured thinking, announces 'Using brainstorming to explore the feature idea', and follows the brainstorming skill steps before providing an opinion.

Install

Download the skill as a ZIP:
https://autogineer.com/agent-skills/openai/using-superpowers/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip using-superpowers.zip -d .agents/skills

Documentation by Jesse Vincent

<SUBAGENT-STOP> If you were dispatched as a subagent to execute a specific task, ignore this skill. </SUBAGENT-STOP>

<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. You cannot rationalize your way out of this. </EXTREMELY-IMPORTANT>

The Rule

Invoke relevant or requested skills BEFORE any response or action — including clarifying questions, exploring the codebase, or checking files. If it turns out wrong for the situation, you don't have to use it.

Before entering plan mode: if you haven't already brainstormed, invoke the brainstorming skill first.

Then announce "Using [skill] to [purpose]" and follow the skill exactly. If it has a checklist, create a todo per item.

Skill Priority

When multiple skills apply, process skills come first — they set the approach, then implementation skills (frontend-design, etc.) carry it out. Brainstorming and systematic-debugging are Superpowers' most common process skills, but the rule holds for any of them.

"Let's build X" → superpowers:brainstorming first, then implementation skills.
"Fix this bug" → superpowers:systematic-debugging first, then domain skills.

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.

Platform Adaptation

If your harness appears here, read its reference file for special instructions:

Codex: references/codex-tools.md
Pi: references/pi-tools.md
Antigravity: references/antigravity-tools.md
Hermes Agent: references/hermes-tools.md

User Instructions

User instructions (CLAUDE.md, AGENTS.md, GEMINI.md, etc, direct requests) take precedence over skills, which in turn override default behavior. Only skip skill workflows or instructions when your human partner has explicitly told you to.

Files

ATTRIBUTION.mdAdded by AutoGineer918 B
LICENSELicence file added by AutoGineer1.0 KiB
SKILL.md3.0 KiB
agents/openai.yaml119 B
references/antigravity-tools.md1.5 KiB
references/codex-tools.md4.7 KiB
references/gemini-tools.md4.5 KiB
references/hermes-tools.md1.9 KiB
references/pi-tools.md1.2 KiB

references/gemini-tools.md

Gemini CLI Tool Mapping

Skills speak in actions ("dispatch a subagent", "create a todo", "read a file"). On Gemini CLI these resolve to the tools below.

Action skills request	Gemini CLI equivalent
Read a file	`read_file`
Read multiple files at once	`read_many_files`
Create a new file	`write_file`
Edit a file	`replace`
Run a shell command	`run_shell_command`
Search file contents	`grep_search`
Find files by name	`glob`
List files and subdirectories	`list_directory`
Fetch a URL	`web_fetch`
Search the web	`google_web_search`
Invoke a skill	`activate_skill`
Dispatch a subagent (`Subagent (general-purpose):` template)	`invoke_agent` with `agent_name: "generalist"` (invocable via `@generalist` chat syntax — see Subagent support)
Multiple parallel dispatches	Multiple `invoke_agent` calls in the same response
Task tracking ("create a todo", "mark complete")	`write_todos` (statuses: pending, in_progress, completed, cancelled, blocked)

Instructions file

When a skill mentions "your instructions file", on Gemini CLI this is GEMINI.md. Gemini CLI loads GEMINI.md hierarchically: global at ~/.gemini/GEMINI.md, project-level files in workspace directories and their ancestors, and sub-directory GEMINI.md files when a tool accesses files in those directories.

Personal skills directory

User-level skills live at ~/.gemini/skills/, with ~/.agents/skills/ as a cross-runtime alias (shared with Codex and Copilot CLI). When both directories exist at the same scope, .agents/skills/ takes precedence. Each skill is a subdirectory containing a SKILL.md (with name and description frontmatter).

Subagent support

Gemini CLI dispatches subagents through the invoke_agent tool, which takes agent_name and prompt parameters. The same dispatch is also surfaced as a chat-syntax shortcut: typing @generalist <prompt> is equivalent to calling invoke_agent with agent_name: "generalist". Built-in agent names include generalist, cli_help, codebase_investigator, and (with browser tooling enabled) browser_agent.

Skills dispatch with Subagent (general-purpose): and either reference a prompt-template file (e.g., superpowers:subagent-driven-development's ./implementer-prompt.md) or supply an inline prompt. On Gemini CLI:

Skill dispatch form	Gemini CLI equivalent
References a `*-prompt.md` template (implementer, task-reviewer, code-reviewer, etc.)	Fill the template, then `invoke_agent` with `agent_name: "generalist"` and the filled prompt
References `superpowers:requesting-code-review`'s `./code-reviewer.md`	`invoke_agent` with `agent_name: "generalist"` and the filled review template
Inline prompt (no template referenced)	`invoke_agent` with `agent_name: "generalist"` and your inline prompt

Prompt filling

Skills provide prompt templates with placeholders like {WHAT_WAS_IMPLEMENTED} or [FULL TEXT of task]. Fill all placeholders before passing the complete prompt to invoke_agent. The prompt template itself contains the agent's role, review criteria, and expected output format — the subagent will follow it.

Parallel dispatch

Gemini CLI supports parallel subagent dispatch. Issue multiple invoke_agent calls in the same response (or multiple @generalist invocations in one prompt) to run independent subagent work in parallel. Keep dependent tasks sequential, but do not serialize independent subagent tasks just to preserve a simpler history.

Additional Gemini CLI tools

These tools are unique to Gemini CLI:

Tool	Purpose
`save_memory` (legacy)	Persist facts across sessions when `experimental.memoryV2 = false`
`get_internal_docs`	Look up Gemini CLI's bundled documentation
`ask_user`	Pose structured questions to the user (text / single-select / multi-select)
`enter_plan_mode` / `exit_plan_mode`	Switch into and out of read-only plan mode
`update_topic`	Update the current conversation's topic / strategic-intent metadata
`complete_task`	Signal that a Gemini subagent has completed and return its result to the parent agent
`tracker_create_task`, `tracker_update_task`, `tracker_get_task`, `tracker_list_tasks`, `tracker_add_dependency`, `tracker_visualize`	Rich task tracker with dependency and visualization support
`read_mcp_resource`, `list_mcp_resources`	MCP resource access

Requirements and compatibility

Written for: OpenAI Codex

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

No issues found by our static scan· No issues found

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by

Jesse Vincent

Publisher

OpenAI (Official)

Distributed by

OpenAI

Source

openai/plugins · plugins/superpowers/skills/using-superpowers · commit d420d13

Licence

MIT License (redistribution allowed)

LICENSE (added by AutoGineer from plugins/superpowers/LICENSE)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-09

AutoGineer is not affiliated with or endorsed by Jesse Vincent or OpenAI.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download using-superpowers.zip