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ehuerta6/ai-setup
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- 27
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Skills in this repository
Showing 27 of 27 collected skills.
Design or evolve reusable AI configuration such as skills, agents, rules, templates, and project instructions without creating unnecessary duplication.
Implement one approved GitHub Issue from scope discovery through a verified, review-ready change.
Review a pull request or completed diff separately against its requirements and against the repository's engineering standards.
Execute Git and GitHub operations using the repository's documented conventions for commits, issues, pull requests, and merging.
Verify a code change using the repository's actual configured checks and report concrete evidence without hiding failures.
Diagnose bugs and regressions by reproducing the exact failure, gathering evidence, testing hypotheses, and verifying the fix.
Decide whether a software project idea solves a worthwhile real problem or should be validated, simplified, or skipped before product discovery.
Create an executable project-local skill for verifying real user-facing application behavior and preserving observable evidence.
Keep a project's verification skill and feature map accurate through source inspection and live exercise without concealing product regressions.
Break an approved spec or large feature into focused, connected GitHub Issues that can be implemented independently by fresh agents.
Turn already-resolved product and engineering decisions into a durable implementation specification without reopening settled decisions.
Coordinate an adaptive end-to-end design phase for a product or major software feature, producing a traceable, approval-ready specification.
Orchestrate evidence-backed, independent analysis and review for consequential decisions with meaningful uncertainty or competing options.
Rigorously clarify product goals, users, scope, workflows, permissions, constraints, and observable behavior without asking the user to design technical internals.
Build a disposable UI or logic prototype to answer a concrete design question before production implementation.
Stress-test a feature, plan, architecture decision, or product idea until the important decisions are explicit and shared.
Rewrite prose so it sounds natural, specific, and appropriate for its actual writer and audience while preserving facts, meaning, and intent.
Design, critique, audit, and refine production frontend UI and UX with strong hierarchy, accessibility, responsive behavior, clear states, and deliberate visual decisions.
Audit a project's AI configuration against current project needs and ai-setup to detect duplication, drift, stale instructions, and missing reusable configuration.
Audit and clean technical writing so it becomes concrete, concise, credible, and free of formulaic AI prose without changing supported facts.
Review completed AI-assisted engineering work to identify concrete improvements to skills, rules, context, tooling, and automated checks.
Plan open GitHub Issues into dependency-aware execution batches, generate prompts for selected batches, and update plans as repository state changes.
Work safely with Firebase projects including Firestore, Authentication, Security Rules, Emulator Suite, Cloud Functions, Storage, indexes, seeds, and trusted server access.
Transfer unfinished work to a fresh agent or session using concise context pointers instead of duplicating existing artifacts.
Roast, review, rewrite, and tailor technical resumes for SWE, AI engineering, backend, full-stack, infrastructure, developer tools, ML, internships, and new-grad roles.
Research a question and compare options using current, traceable evidence and explicit tradeoffs.