Evaluating Superpowers: Does the Coding Agent Checklist Justify the Token Cost?
The Superpowers plugin promises to stop AI coding agents from breaking your codebase. We analyze its performance, token costs, and when developers should actually use it.
Coding agents are notorious for overconfidence. You ask an AI assistant to add a simple CSV export to a report, it claims "done" without asking a single follow-up question, and suddenly adjacent pages on your site no longer load. To address this tendency to break codebases, developers are turning to "Superpowers," a popular GitHub repository with approximately 294,000 stars. Rather than giving agents entirely new technical capabilities, Superpowers acts as a structured preflight checklist to keep AI coding assistants disciplined.
Structuring the Agent Workflow
Superpowers consists of 15 skills designed for Claude Code, though the framework also supports other environments including Cursor, Codex, Copilot CLI, and Gemini CLI. To prevent context bloat, only a single skill called using-superpowers (roughly 490 words) is loaded at the start of a session. The remaining 14 skills reside on disk until they are explicitly required by the task at hand.
When a task begins, Superpowers guides the agent through a strict four-stage process. First, the agent proposes a design and waits for user approval. Second, it generates a detailed plan—which must also be approved. Third, it writes tests before writing the actual code. Finally, the agent must run the entire test suite before declaring the task complete.
A key component of the planning phase is the "Review Focus" section, which highlights up to five areas implied by the specification but not covered by existing tests. In Native mode, a single agent handles the work and a separate agent reviews the branch at the end. Version 6.4.1 rebuilt this mode after developers realized the original implementation performed no better than using no plugin at all. For higher-risk tasks, Subagent-driven mode spins up a new agent for every individual subtask, though this increases operational costs.
The Cost and Performance Trade-offs
Adding rigid guardrails to AI agents naturally impacts execution speed and token consumption. In June 2026, researcher Norbert Laszlo conducted an independent benchmark of 500 tasks using Codex to evaluate the plugin's performance. The results showed that accuracy only saw a minor shift, moving from 45.6% to 47.8%—a change within the margin of error.
However, the structured workflow came with a resource cost. Token usage jumped by roughly 40%, rising from 1.56 million to 2.18 million tokens per task. Additionally, each task took an average of 74 seconds longer to complete. While cached tokens can help mitigate some of these financial costs, the extra time investment remains a consideration.
For developers looking to benchmark these behaviors across various LLMs without paying premium rates for multiple individual platforms, they can try top AI models cheaply through one API at https://apixoai.online. This makes it easier to measure how different models handle the extra token overhead introduced by structured agent frameworks.
What it means for developers
Superpowers is not a universal fix for every coding task. Instead, its value depends heavily on the scope of the project.
It is highly recommended for:
- Building new features across multiple files or starting projects from scratch, where agents otherwise tend to write code prematurely.
- Long, unattended runs where you need assurance that the agent actually ran tests before finishing.
- Team environments where having a standardized, named process is easier to manage than individual custom prompts.
Conversely, the plugin is unnecessary for minor edits of under 20 lines, quick exploratory questions, or fixing bugs in external repositories, where benchmarks showed no accuracy improvements.
If you want to adopt the core philosophy without installing the plugin, you can add custom instructions to your CLAUDE.md file. The maintainers suggest rules such as skipping plans for edits under 20 lines, requiring a full test command run to define "done," and forcing the agent to stop and rethink after three failed attempts. Developers should also note that the plugin requests a logo from the authors' server, which shares the installed version number; this can be disabled by setting SUPERPOWERS_DISABLE_TELEMETRY to true.
Source: What is Superpowers? Where it is a Must, and Where It Is Not — Towards AI. Written by the Apixo team from that report.
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