Loading...
Loading...
Found 2,164 Skills
eBPF skill for Linux observability and networking. Use when writing eBPF programs with libbpf or bpftrace, attaching kprobes/tracepoints/XDP hooks, debugging verifier errors, working with eBPF maps, or achieving CO-RE portability across kernel versions. Activates on queries about eBPF, bpftool, bpftrace, XDP programs, libbpf, verifier errors, eBPF maps, or kernel tracing with BPF.
Use when fixing, editing, changing, or debugging existing TypeScript code and keeping changes small and proportional to what was touched.
Validates YAML syntax and structure for all .yml and .yaml files in the project. Identifies common issues like invalid syntax, indentation errors, missing keys, type mismatches, and provides fixes. Use when editing, creating, or debugging YAML configuration files.
Structure a pygame (pygame-ce) game in Python: the init/event/update/draw loop, delta-time movement, Surface/Rect blitting, keyboard/mouse input, and Sprite/Group management with collision. Use when building or debugging a pygame game — when the user mentions pygame, pygame-ce, the game loop, blit, Surface, Rect, sprite groups, or clock.tick. Targets pygame-ce.
Opt-in evidence-first causal diagnosis for bugs, browser or app/device failures, flaky behavior, and performance regressions. Activate only when the user explicitly invokes `$diagnose` or explicitly asks to use the named diagnose skill. Do not activate merely because the user mentions a bug, asks why something failed, requests debugging or a fix, or describes unexpected behavior. Once explicitly invoked, locate likely causes, instrument relevant boundaries with extensive structured logging, reproduce the issue, analyze the collected logs, rank causes with confidence scores, and pursue 100% operational confidence while probes can increase confidence.
Expert model design decisions for iOS/tvOS: when DTO separation adds value vs overkill, validation strategy selection, immutability trade-offs, and custom Codable decoder design. Use when designing data models, implementing API contracts, or debugging decoding failures. Trigger keywords: Codable, DTO, domain model, CodingKeys, custom decoder, validation, immutable, struct, mapping, JSON decoding
Evaluate how well a codebase supports autonomous AI development. Analyzes repositories across eight technical pillars (Style & Validation, Build System, Testing, Documentation, Dev Environment, Debugging & Observability, Security, Task Discovery) and five maturity levels. Use when users request `/readiness-report` or want to assess agent readiness, codebase maturity, or identify gaps preventing effective AI-assisted development.
Manage SLAS (Shopper Login and API Access Service) clients for B2C Commerce (SFCC/Demandware) with the b2c cli. Use when configuring shopper authentication, creating API clients for PWA/headless, managing OAuth scopes (including custom scopes like c_loyalty), or debugging token issues. SLAS is for shopper (customer) authentication, not admin APIs.
Generate and validate Apex test classes with TestDataFactory patterns, bulk testing (251+ records), mocking strategies, assertion best practices, and disciplined test-fix loops. Use this skill when creating new Apex test classes, improving test coverage, debugging and fixing failing Apex tests, running test execution and coverage analysis, or implementing testing patterns for triggers, services, controllers, batch jobs, queueables, and integrations. Triggers on *Test.cls, *_Test.cls files, sf apex run test workflows, coverage reports, test-fix loops. Do NOT trigger for production Apex code (use generating-apex) or Jest/LWC tests.
Troubleshoots Google Cloud Gemini Enterprise Agent Platform issues (Agent Gateway, Registry, Identity, Policies, Model Armor, Identity-Aware Proxy (IAP)). Use when agent requests fail with 403 (especially unauthorized egress), Agent Runtime queries return 500, or gateway/IAP logs show permission errors. Don't use for general Google Cloud Identity and Access Management (IAM) debugging or networking issues unrelated to the Agent Platform stack.
Monitors and troubleshoots GKE TPU workloads, nodes, and node pools using GKE system metrics and PromQL. Use when monitoring TensorCore duty cycle, TPU memory, node readiness, multi-host TPU node pool availability, host maintenance or preemption interruptions, and calculating MTTR or MTBI metrics for GKE TPUs. Don't use for general non-TPU GKE workload monitoring or non-metric TPU debugging.
Research and advise on the best way to approach a software project, including architecture, tech stack, implementation strategy, pricing/operating-cost tradeoffs, benchmark research, and comparisons with similar real-world projects. Use before building, mid-build, or after completion when the user asks for project strategy, optimal approach, research comparables, similar projects, stack selection, vendor/service choice, repo analysis, architecture critique, implementation feedback, or a prioritized improvement plan. Avoid for narrow single-bug debugging or isolated file edits unless the user asks for broader project direction.