Browse Skills

Hermes Code Review runs a bug-first, evidence-grounded review of code, diffs, and claims. Use it when you need ranked findings, test gaps, and a clear ship or no_ship verdict.

Profile Memory helps investigate Sidecar memory growth, goroutine leaks, open file accumulation, and CPU hotspots with pprof and system tools. Use it when debugging leaks, unresponsive plugins, or performance issues.

Flutter App Testing runs Dart analysis, formatting, and Flutter tests for the mobile app. Use it when validating Flutter changes and writing tests for widgets or logic.

Self Review checks code changes before a task is finished by collecting diffs and, for larger changes, asking a code-reviewer subagent to review them. Use it to catch issues before committing or closing work.

Test Bridge documents how to run Bridge Server unit tests, type checks, and optional coverage. It also specifies Vitest test file layout, imports, and patterns for writing tests.

Triage reviews a GitHub Issue or PR by number and reports the request summary, implementation difficulty, duplicate features, and whether it should be addressed. Use it when deciding priority or response for an issue or pull request.

Code Review reviews Python code for security, correctness, and best practices. Use it to assess structure, error handling, type hints, and documentation before merging changes.

Code Review performs a systematic review for correctness, security, performance, style, and testing gaps. Use it to inspect changed code and report concrete issues with suggested fixes.

Performant Code helps you write efficient code for large inputs and tight limits. Use it when you need to avoid timeouts, reduce memory use, or choose faster data access and algorithm patterns.

Refactor improves code structure without changing external behavior. Use it to extract helpers, simplify conditionals, rename unclear code, and reorganize modules while keeping tests passing.

Systematic Debugging provides a step-by-step loop to reproduce, isolate, diagnose, fix, and verify bugs. Use it when code fails, gives wrong output, times out, or behaves differently across environments.

Test Generator generates pytest test cases for Python functions and classes. Use it to cover happy paths, edge cases, errors, and async code.