Deepen an existing system or UI spec so boundaries, lifecycle rules, failure handling, and validation are strong enough for planning. Use when the user wants Harness Engineering spec hardening or a requirements review pass before planning.

Implement HTTP networking with Dio including interceptors, retry logic, and response caching. Use when building API clients, configuring authentication headers, or handling network errors gracefully.

Build type-safe native platform integrations using MethodChannels, EventChannels, and Pigeon. Use when communicating with Android/iOS native code, implementing federated plugins, or bridging platform-specific APIs.

Extract design systems from reference UI images and generate implementation-ready UI design prompts. Use when users provide UI screenshots/mockups and want to create consistent designs, generate design systems, or build MVP UIs matching reference aesthetics.

Choose, run, rerun, or debug OpenClaw tests, CI checks, Docker E2E lanes, release validation, and the cheapest safe verification path.

Fix only small, high-certainty OpenClaw bugs from a pasted issue/PR list after deep code review.

Find or repair small high-confidence non-SDK-boundary OpenClaw bugfix PRs until five are landable.

Use when you need programmatic JDBC in Quarkus — Agroal DataSource, parameterized SQL, transactions, batching, and Dev Services. This should trigger for requests such as Review JDBC or SQL data access in a Quarkus project; Improve transactions and parameter binding for Quarkus JDBC; Translate SQLException to domain exceptions or stream large result sets; Fix CDI self-invocation bypassing @Transactional in Quarkus. Part of cursor-rules-java project

Use when you need the Jira CLI (`jira`) to verify installation, configure Jira Cloud access, list issues (all or by JQL) as markdown tables, and fetch issue descriptions and comments for analysis. Uses an interactive install gate - if `jira` is missing, ask whether to show installation guidance before any issue commands. This should trigger for requests such as jira issue list; List Jira issues; Jira JQL issue query; jira issue view comments; Jira CLI issue workflow. Part of cursor-rules-java project

Parses Kubernetes API server audit logs (JSON lines) to detect exec-into-pod, secret access, RBAC modifications, privileged pod creation, and anonymous API access. Builds threat detection rules from audit event patterns. Use when investigating Kubernetes cluster compromise or building k8s-specific SIEM detection rules.

Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query to detect suspicious administrative operations, impossible travel, privilege escalation, and resource modifications. Builds KQL queries for threat hunting in Azure environments. Use when investigating suspicious Azure tenant activity or building cloud SIEM detections.

Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts. Uses pandas for statistical analysis of request patterns and anomaly detection. Use when investigating API abuse or building API-specific threat detection rules.

Use when main results pass result-to-claim (`claim_supported = yes` or `partial`) and ablation studies are needed for paper submission. A secondary Codex agent designs ablations from a reviewer's perspective; the local executor reviews feasibility and implements.

Optimizes application performance. Use when performance requirements exist, when you suspect performance regressions, or when Core Web Vitals or load times need improvement. Use when profiling reveals bottlenecks that need fixing.

Use when creating new skills, editing existing skills, or verifying skills work before deployment

Use when you need to set up Java application profiling to detect and measure performance issues — including automated async-profiler v4.0 setup, problem-driven profiling (CPU, memory, threading, GC, I/O), interactive profiling scripts, JFR integration with Java 25 (JEP 518, JEP 520), or collecting profiling data with flamegraphs and JFR recordings. This should trigger for requests such as Improve the code with profiling; Apply Profiling; Refactor the code with profiling; Add profiling support. Part of cursor-rules-java project

Use when you need to generate an AGENTS.md file for a Java repository — covering project conventions, tech stack, file structure, commands, Git workflow, and contributor boundaries — through a modular, step-based interactive process that adapts to your specific project needs. This should trigger for requests such as Create AGENTS.md; Update AGENTS.md file; Add agent instructions. Part of cursor-rules-java project

Use when you need to verify Java performance optimizations by comparing profiling results before and after refactoring — including baseline validation, post-refactoring report generation, quantitative before/after metrics comparison, side-by-side flamegraph analysis, regression detection, or creating profiling-comparison-analysis and profiling-final-results documentation. This should trigger for requests such as Verify performance fix; Verify the performance; Verify the memory; Verify the threading. Part of cursor-rules-java project

Use when you need to generate Architecture Decision Records (ADRs) for a Java project through an interactive, conversational process that systematically gathers context, stakeholders, options, and outcomes to produce well-structured ADR documents. This should trigger for requests such as Generate ADR; Create Architecture Decision Record; Document architecture decision; Architecture Decision Record for Java. Part of cursor-rules-java project

Render a documentation-style Cursor Canvas that organizes architecture notes, API references, walkthroughs, and how-tos into a navigable layout with sections, tables of contents, and cross-references. Use when the user asks for a docs canvas, documentation overview, architecture walkthrough, API reference page, or wants to render structured documentation as an interactive canvas.