Writes a high-quality CLAUDE.md, .cursorrules, or .windsurfrules file that gives a coding agent the right project context, conventions, and constraints to work effectively.

Designs an eval suite for an LLM agent or pipeline including success metrics, trajectory scoring, LLM-as-judge setup, and regression test cases.

Reads a codebase or system description and produces a clear, structured architecture overview with diagrams.

Takes a long-form article and repurposes it into multiple formats: tweet thread, LinkedIn post, TL;DR, and key quotes.

Designs a secure authentication and authorization flow for any application, covering login, sessions, roles, and edge cases.

Generates a detailed, SEO-optimized blog post outline with H2/H3 structure, key points per section, and a hook.

Compares two versions of a codebase or API and flags all breaking changes with migration hints.

Systematically diagnoses bugs by tracing execution flow and identifying root causes vs symptoms.

Recommends the right caching layer, TTL strategy, and invalidation approach for any application bottleneck.

Maintains and formats a CHANGELOG.md following Keep a Changelog conventions from git history or PR list.

Reviews database schemas for normalization issues, missing indexes, naming inconsistencies, and scalability risks.

Generates production-ready docker-compose.yml files for any application stack.

Audits a codebase or docs folder and lists everything that is undocumented, outdated, or unclear.

Systematically identifies edge cases and boundary conditions for any function, API, or user flow.

Parses raw error logs and produces a concise, prioritized summary of unique issues with root cause hints.

Diagnoses why tests pass inconsistently and suggests fixes for timing, ordering, and state isolation issues.

Generates conventional commit messages from staged changes or a diff.

Reviews an AI-generated response or LLM application output for factual risks, hallucination patterns, and confidence calibration issues.

Designs a hybrid retrieval pipeline combining dense vector search and BM25 sparse search with reciprocal rank fusion, and explains when to use each configuration.