AI search engines may overlook useful content when its answers, evidence, and structure are difficult to extract. This skill audits visibility and recommends focused improvements.

Ad teams need many platform-ready variations without losing evidence, brand fit, or review clarity. This skill creates grounded copy, concepts, test plans, and review pages.

Tree-sitter integrations often fail on malformed code, language differences, and inefficient traversal. This skill provides reusable parsing, query, visitor, error-handling, and optimization patterns.

JSON can consume excessive prompt tokens when records repeat the same keys. This skill converts suitable structures into compact TOON and validates format rules.

Creating consistent test skeletons across mixed-language repositories takes time. This skill analyzes public symbols and generates framework-specific scaffolds with fixtures, mocks, and TODO markers.

Supabase projects can expose data when RLS, storage, and realtime rules are incomplete. This skill provides reusable security patterns, migrations, client examples, and review checklists.

Repository conventions are often scattered across guides, formatter settings, linter rules, hooks, and CI files. This skill consolidates those sources into one evidence-based standards summary.

Project teams may miss relevant AI development skills for their frameworks and workflows. This skill maps detected technologies to recommendations and optional project templates.

Specification requirements are difficult to locate and trace across repositories. This skill extracts requirement IDs, titles, paths, links, and hashes into a sorted manifest.

Long-running CLI commands can occupy the active session and hide progress. This skill opens a separate terminal after checking command help.

Starting separate AI coding sessions across different CLIs requires platform-specific commands. This skill launches supported agents in new terminals and can capture their output.

Interactive tools and long-running commands can block the current coding session. This skill opens them in separate terminals and optionally captures their output.

Database schemas and application models can diverge, causing runtime errors and failed deployments. This skill compares migrations, schemas, and ORM models to produce prioritized alignment reports.

Research questions often require current web evidence, local documentation, and code examples. This skill coordinates those sources and synthesizes findings with clear confidence labels.

Teams often write inconsistent tests that are hard to maintain. This skill gives Claude, Codex, and Claude Code a shared testing structure for fixtures, mocks, coverage, and CI scope.

Research tasks often lose scope, citations, and source quality. This skill gives Claude, Codex, and Claude Code a repeatable research workflow.

Teams lose time when models, APIs, and documentation use inconsistent business terms. This skill gives Claude, Codex, and Claude Code a shared domain glossary and relationship map.

Code changes often leave README files, changelogs, and docstrings outdated. This skill reviews implementation changes and updates affected documentation using repository conventions.

Managing several AI coding CLIs requires provider routing, permissions, isolation, and result collection. This guide defines a repeatable Claude Code workflow for coordinated agent execution.

Selecting the right AI provider for each task is difficult and costly. This skill routes work by capability, availability, privacy, and cost.