Claude can write frontend code. What it needs is a design system vocabulary to write CONSISTENT frontend code. This skill gives it that vocabulary, so every button, form, and layout follows the same rules across your entire app.
A professional technical editor's review for your docs. Catches missing context, unclear writing, and unverifiable claims in READMEs, API docs, and changelogs before they ship — with a PASS/REVISE verdict and a prioritized fix list.
1
technical-writingdocumentationreadme+6
AGENTS.md and llms.txt Writer Reviewer — Make Your Repo and Site Agent Ready
Write and review the docs AI agents actually read — AGENTS.md for your repo and llms.txt for your site. Drafts them from scratch or audits existing ones for completeness, clarity, and wasted context, with a PASS or REVISE verdict.
Claude defaults to complex. This skill does not let that happen. Before your session ships a 400-line solution to a 20-line problem, the simplicity filter stops it and asks: does this actually need to be this complex?
2
code-reviewclean-codeperformance-audit+2
API Docs Writer — Generate Clear, Accurate API Reference from Your Code or OpenAPI Spec
Generate consistent API reference docs from your code, OpenAPI spec, or route handlers — per-endpoint parameters, real request and response examples, error codes, auth, and copy-pasteable curl, written for the developer calling the API.
1
api-documentationrest-apitechnical-writing+6
README Writer — Generate a Professional, Reader Ready README (Not a Template Dump)
Generate a complete, reader-ready README from your code and project details — not a template dump. It leads with what the project is and why, gives a quickstart that actually runs, and includes only the sections that apply.
1
documentationreadmemarkdown+6
Git Writing Suite — Commit Messages, PR Descriptions, and Release Notes Developers Actually Read
Turn your diffs and commit history into commit messages, PR descriptions, and release notes that reviewers and users actually read. One skill, three jobs — conventional-commit compliant, reviewer-ready, and written in plain language.
1
gitpull-requestchangelog+6
Monolith to Modular Architecture Migration Planner
Creates phased modernization plans for transforming monolithic applications into modular monoliths, service-oriented systems, or microservice-ready architectures without risky rewrites.
Design and write the eval suite for your LLM-powered feature — the metrics that match your failure modes, a golden dataset plan with starter cases, anchored rubrics, LLM-as-judge prompts with the known bias mitigations, and pass/fail gates wired for CI.
1
evalsllm-evaluationllm-as-judge+6
Agent Hooks Security and Quality Gate — Audit Your Pre and Post Tool Use Hooks Before They Ship
Adversarially audit your agent hooks before you trust them. Catches command injection, secret leakage, over-broad matchers, destructive actions, and blocking-logic mistakes in pre/post-tool-use, prompt, and stop hooks — with a PASS or REVISE verdict and severity-ranked fixes.
Teaches AI coding agents to implement production-grade structured logging, error handling, and observability from the first line of code. For developers deploying agent-built services who are tired of debugging black boxes.
Find the code that quietly runs up your LLM bill: uncapped generations, model calls looping with no limit, an expensive model doing a trivial job, and whole files stuffed into prompts. Read-only, every finding explained in plain English.
Check an AI-built app for work that looks finished but is not: leftover TODOs and stubs, fake or mock data returned as real, errors quietly swallowed, placeholder content, and endpoints that fake success. Read-only, every finding explained in plain English for non-coders.
1
code-reviewquality-assurancepython+2
Background Agent Task Brief Writer — Delegate to Unattended Agents Without the Surprise PR
Write the delegation brief that lets a background or async agent succeed unattended — precise goal, hard constraints, testable acceptance criteria, a verification plan, and stop-and-escalate rules. Turns "go fix the flaky tests" into a spec an agent can actually execute.
1
delegationbackground-agentsasync-agents+6
LLM Cost and Token Economics Modeler — Project Your Agent's Spend and Cut It in Half
Model what your LLM app or agent will cost, find where the money goes, and get a plan to cut it. Per-request and monthly projections, ranked cost drivers, an optimization plan with estimated savings, and unit economics against your pricing — with the arithmetic shown.
Reviews your code for bugs, security vulnerabilities, logic errors, performance issues, and style violations. Organizes findings by severity and suggests fixes with code examples.
Writes clear pull request descriptions by analyzing your branch diff. Covers what changed, why, how, and what to test. Works with GitHub, GitLab, and Bitbucket.