Marketplace

Use when adding, upgrading, or auditing third-party packages: judge vulnerabilities, maintenance health, and supply-chain risk before they ship.

Use when a failure's cause is unknown: a hypothesis-driven protocol from symptom to confirmed root cause, with evidence trail and regression test.

Find and safely remove dead code: unreachable branches, unused exports, orphaned files, and stale configuration.

Design data warehouse schemas: star/snowflake schemas, slowly changing dimensions, materialized views, and query optimization.

Design data quality monitoring: anomaly detection, schema validation, freshness checks, and data contracts between teams.

Design robust data pipelines: ingestion patterns, transformation stages, schema evolution, and data quality monitoring.

Design data governance frameworks: data classification, lineage tracking, access policies, retention, and compliance mapping.

Systematically clean a messy dataset with profiling, ordered fixes, validation, and a provenance log; use before analyzing or merging untrusted data.

Review cryptographic implementations: algorithm selection, key management, random number generation, and protocol-level flaws.

Audit cloud infrastructure for cost optimization: right-sizing, reserved capacity, storage tiers, and waste elimination.

Design conversational analytics interfaces: NL-to-SQL, query disambiguation, result narration, and data storytelling.

Optimize how context is assembled for LLM calls: system prompt design, few-shot example selection, context pruning, and token budget management.

Scan and harden container images: base image vulnerabilities, runtime permissions, distroless patterns, and admission policies.

Audit application configuration: environment variables, secrets management, config validation, and environment parity.

Audit code for race conditions, deadlocks, and thread safety issues in async and multi-threaded code.

Design ergonomic component APIs: prop design, composition patterns, accessibility defaults, and forward compatibility.

Conduct systematic competitor analysis: feature matrices, positioning maps, moat assessment, and strategic gap identification.

Use when reviewing a diff, PR, or staged changes: a five-pass protocol that yields severity-ranked findings with concrete failure cases.

Create comprehensive onboarding documentation for any codebase: architecture maps, data flow diagrams, and gotchas for new developers.

Use when designing or migrating a workload onto Cloudflare's edge: Workers, R2, D1, KV, Durable Objects, Cache Rules, WAF, and origin cutover.

Use when CI pipelines are flaky, slow, or failing intermittently; diagnoses root causes from logs and configs and prescribes durable fixes.

Optimize CI pipeline caching: layer caching, dependency caching, test splitting, and parallel execution strategies.

Analyze customer churn: cohort analysis, churn signals, at-risk scoring, retention experiments, and win-back strategies.

Invoke when building or tuning a RAG/semantic-search pipeline's chunking: pick strategy, chunk size, and overlap validated against retrieval metrics.