Four Free Claude Code Skills for Prompt Clarity, Tutorials, and Bug Hunting
A Reddit user shared four free Claude Code skills (Apache 2.0, no paid tier) built while developing Stuffolio, a Universal iOS/iPadOS/macOS app. Each skill is available with sample outputs on GitHub.
prompter
Rewrites your Claude Code prompt for clarity before execution. It resolves ambiguous references like “that file” to a file path, sharpens vague verbs, and restructures stacked questions. Crucially, it skips rewriting when the prompt is already clear, avoiding friction on simple prompts. Includes worked examples across 8 categories.
tutorial-creator
Turns a file from your own project into an annotated reading tutorial with vocabulary tracking, pre- and post-tests, and prerequisite gap analysis. Language-agnostic — works with any codebase. Sample outputs: a starter walkthrough and a more advanced one.
bug-echo
After you fix a bug, bug-echo reads your fix, confirms the anti-pattern, then scans the entire codebase for other instances of the same error. Each match is read in context and classified as BUG / OK / REVIEW. It honors #if os(...) blocks, so Universal codebases don’t get false positives across platforms. Sample report from a real run.
bug-prospector
Forward-looking audit that runs 7 analysis lenses: assumptions, state machines, boundaries, data lifecycle, error paths, time-dependent bugs, and platform divergence. It asks upfront whether the project is iOS, macOS, or Universal so findings respect your platform set. Works well combined with bug-echo: run prospector before releases, echo after prospector fixes. Sample report.
Who it's for: Developers using Claude Code on multi-platform or complex codebases who want automated prompt refinement, codebase-wide bug detection, and pre-release auditing.
📖 Read the full source: r/ClaudeAI
👀 See Also
ClawCodex /advisor Mode: Pair Cheap Worker with Expensive Reviewer to Cut Costs Without Losing Quality
Open-source Python coding agent ClawCodex adds an /advisor mode that pairs a cheap worker model (e.g., Haiku) with an expensive reviewer (e.g., Opus) at decision points, cutting costs several-fold without sacrificing architectural judgment.
Open-sourced self-healing skill for AI agents detects and fixes failures automatically
A new open-source skill enables AI agents to automatically detect failures, diagnose root causes, and implement fixes. It includes a failure scanner for crons, sub-agents, and deploy logs, plus a database that learns from previous fixes.
Surgical GitHub Extraction: A Claude Skill to Fetch One Function, Not the Whole Repo
A new open-source Claude Skill named surgical-github-extraction stops Claude Code from cloning entire repos when you only want one function or pattern. It reads the README, pulls 1–3 raw source files, and lifts the smallest useful unit with a provenance comment.
NLA Transforms Gemma 3’s Internal Activations into Readable Text for Any Token
Anthropic released Natural Language Autoencoders (NLA) that decode a model’s internal state into text. Paired with Gemma 3, the Auto Verbalizer explains what the model was “thinking” for any generated token. Weights are on Hugging Face; demo on Neuronpedia.