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Found 2,772 Skills
Harden the test surface after `/cook` — map changed behavior to tests, find weak assertions and missing boundaries, and add focused hardening tests. Use when the user wants the tests strengthened before review or shipping — phrases like "press the changes", "harden this", "check coverage", "strengthen the tests", "are the tests good enough", "press before /age", "/press". Use even when the user wants to "tighten things up" before review. Do NOT use to add broad new behavior — only corrective fixes that hardening tests force.
Improves Java test quality with JUnit 5, AssertJ, Mockito, fixtures, parameterized tests, integration scope, coverage judgment, and maintainable assertions. Use when adding Java tests, reviewing Java test classes, improving Java coverage, or designing Java unit and integration tests.
When behavior is emergent across components—fixes elsewhere break, loops/delays dominate—map boundary, stocks/flows, feedback, archetypes, then rank leverage.
Generate, execute, and analyze tests for codebases, covering unit, integration, and end-to-end testing with coverage reporting. Use when the user requests testing or provides relevant inputs for this workflow.
Design ObjectStack AI skills, tools, knowledge sources, conversations, model registry entries, and MCP integrations. Use when the user is adding `*.skill.ts` / `*.tool.ts`, configuring an LLM provider, wiring agent tools, or indexing ObjectStack data as a knowledge source for RAG. Agents themselves are platform-internal (`ask` / `build`) — third parties extend them via skills and tools, not by authoring `*.agent.ts`. Do not use for general LLM prompting questions unrelated to ObjectStack metadata.
Audit a whole regression suite and prune/restructure it with evidence: per-test coverage fingerprinting, AST near-duplicate clustering, CI-history mining for never-failing and flaky tests, prune decision rules (redundant/obsolete/low-value/keep), smoke/core/extended tiering by risk and defect-detection history, and a defensible "what we deleted and why" record. Deletion is destructive — quarantine and human sign-off are mandatory. Use when: "audit the test suite," "prune redundant tests," "find duplicate tests," "which tests can we delete," "restructure into smoke/core/extended," "is this test pulling its weight," "shrink the regression suite." Not for: Judging whether an individual test is WELL-WRITTEN (smells, assertions) — that is ai-qa-review. Healing one flaky test at runtime — that is test-reliability. Bulk selector regeneration after a UI refactor — that is selector-drift-recovery. Related: ai-qa-review, coverage-analysis, test-reliability, risk-based-testing, qa-project-context.
Build RAG / unstructured-document evaluation datasets and demo documents (e.g. for Knowledge Assistant) on Databricks: generate synthetic PDFs locally, upload to Unity Catalog volumes, and pair each document with test questions for retrieval evaluation.
End-to-end Dynatrace alerting lifecycle — anomaly detector setup and model selection (static threshold, adaptive baseline, seasonal baseline), alert event storage in Grail, problem grouping and denoising by root cause analysis, and workflow-based notification routing (email, Slack, ServiceNow, webhook). Use when configuring alerting, choosing between detector types, querying alert event history, understanding why alerts merged into a problem, or setting up problem-triggered notifications.
Baidu Netdisk (Baidu Cloud) file management skill. Upload, download, transfer, share, and list files. Use when user wants to manage files on Baidu Netdisk cloud storage.
Analyze codebase to design and implement comprehensive test coverage — top-down code analysis, bottom-up test design, edge case focus, existing test audit, and agent team execution
This skill should be used when the user asks to "write a fragment shader", "make a GLSL gradient/noise/plasma background", "create an image transition (dissolve, displacement, glitch)", "add distortion or chromatic aberration", "build an SDF shape shader", "wire up a Three.js ShaderMaterial with uniforms", or "do GPU post-processing". Covers GLSL fragment shaders, noise/fbm, SDFs, domain warping, transitions, and Three.js integration.
Test AI/LLM features that ship in your product. Covers prompt regression testing, response quality evaluation, tool-call validation, hallucination and RAG grounding checks, nondeterministic-output strategies, red-team/safety scans, eval frameworks, and agent-as-target injection (indirect injection via tool output / RAG / scan reports, self-propagating payloads, data exfiltration via an agent) plus a bundled detector for untrusted content. Use when: "test our LLM feature," "prompt regression test," "eval framework," "hallucination test," "RAG grounding," "nondeterministic output," "AI feature testing," "red-team our chatbot," "indirect prompt injection," "agent reading untrusted tool output," "production AI quality." Not for: using AI to generate your own test code — use ai-test-generation. Not for: classifying CI failures with AI — use ai-bug-triage. Not for: EU AI Act / GDPR conformity of an AI feature — use compliance-testing. Not for: canary/flag rollout of an AI feature — use testing-in-production. Related: ai-test-generation, ai-qa-review, api-testing, compliance-testing, security-testing, risk-based-testing, test-data-management.