Loading...
Loading...
Found 105 Skills
Jmeter Test Plan Creator - Auto-activating skill for Performance Testing. Triggers on: jmeter test plan creator, jmeter test plan creator Part of the Performance Testing skill category.
Memory Profiler Setup - Auto-activating skill for Performance Testing. Triggers on: memory profiler setup, memory profiler setup Part of the Performance Testing skill category.
Profile-driven performance optimization with behavior proofs. Use when: optimize, slow, bottleneck, hotspot, profile, p95, latency, throughput, or algorithmic improvements.
Database Query Profiler - Auto-activating skill for Performance Testing. Triggers on: database query profiler, database query profiler Part of the Performance Testing skill category.
Percentile Analyzer - Auto-activating skill for Performance Testing. Triggers on: percentile analyzer, percentile analyzer Part of the Performance Testing skill category.
Use when running controlled perf experiments to validate hypotheses.
Artillery Config Generator - Auto-activating skill for Performance Testing. Triggers on: artillery config generator, artillery config generator Part of the Performance Testing skill category.
Go testing patterns and methodology: table-driven tests, t.Run subtests, t.Helper helpers, mocking interfaces, benchmarks, race detection, and synctest. Use when writing new Go tests, modifying existing tests, adding coverage, fixing failing tests, writing benchmarks, or creating mocks. Triggered by "go test", "_test.go", "table-driven", "t.Run", "benchmark", "mock", "race detection", "test coverage". Do NOT use for non-Go testing (use test-driven-development instead), debugging test failures (use systematic-debugging), or general Go development without test focus (use golang-general-engineer directly).
Add tree-sitter language support to codegraph end-to-end — wire the grammar + extractor, write tests, then benchmark extraction quality and retrieval value on 3 popular real-world repos. Use when the user runs /add-lang <language> or asks to add/support a new language (e.g. Lua, Elixir, Zig, OCaml) in codegraph.
Identify, validate, and ship production-safe Node.js optimizations with execution time as the primary objective. Use when users ask to reduce latency (p50/p95/p99), improve throughput, and then reduce CPU/memory/event-loop lag/FD pressure or retry amplification, using one-PR-per-improvement workflows with benchmarks.
Optimizes algorithms via autoresearch loop: benchmark, research, hypothesize, keep/discard
Benchmark CodeGraph retrieval quality on a real codebase by comparing agent behavior with vs without CodeGraph. Use when the user runs /agent-eval or asks to test, benchmark, audit, or validate a codegraph version (the local dev build or a published npm version) against a language's repo.