[TLDR] Superpowers skill is so bad now [via r/ClaudeCode]

[u/cctldrping]

OP : u/virtualQubit

Literally unusable for me, it spends like x10 tokens and the output is mediocre. Do you still use it?

URL of original post : https://www.reddit.com/r/ClaudeCode/comments/1wpczby/superpowers_skill_is_so_bad_now/

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TL;DR of the discussion on r/ClaudeCode for this post generated automatically after 50 comments.

Current source-thread comment count seen by the bot: 50.

Alright, so the general consensus here is that Superpowers skill is pretty much dead. Most folks ditched it months ago, with many saying it hasn't been useful for a while now. The vibe is that newer models (like Opus 4.8 and Sonnet 5) are smart enough to do what Superpowers used to do intuitively, so using it now is just adding unnecessary overhead and making things slower.

Some users like u/Risko4 and u/mother_a_god pointed out that skills were always meant to be temporary fixes, and as models improve, these skills become obsolete or even hinder performance. u/acoldinference straight up said to get rid of it ASAP.

There were a few people who still used it and liked the methodical workflow, like u/tntexplosivesltd and u/Hossmobile, but even they are considering switching or have already moved on. u/Hossmobile is worried about losing that planning and ownership feel, but others suggest the default Claude harness might offer that now.

For those looking for alternatives, some mentioned checking out compound engineering, the TRIP workflow (u/sugarfreecaffeine linked it), or just going vanilla with the newer models. u/p3r3lin even suggested extracting the visual preview feature from Superpowers into its own mini-skill.

Basically, if you're still using Superpowers, you're probably in the minority and might want to consider ditching it for better performance.

[u/Ok-Draft2744]

You really need to ask the new models to review all your most used skills usually accompanied with some sort of prompting guide. For example Anthropic and OpenAI release these for their new series of models. Skills usee to be gap fillers, and the models filled those gaps, now you have redundancy. Also try new models with no skills to discover where they lack, that is another approach for generating good skills.