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Found 1,473 Skills
Ability to design, analyse, test, and maintain mechanical systems and components that meet defined functional, safety, and performance requirements. Includes applying engineering principles to materials, structures, thermodynamics, fluid mechanics, and motion systems; producing and interpreting technical designs and specifications; validating designs through analysis and testing; and supporting manufacture, operation, and lifecycle management. Applies across industrial, infrastructure, energy, manufacturing, and product contexts and is independent of specific tools or industries, with human accountability retained for safety, compliance, and outcomes.
Use this skill when building Python desktop applications using PySide6 with strict MVC architecture where all UI is defined by .ui files. Covers architecture patterns, controller/model/view separation, signal handling, and .ui file workflows.
Specify micro-interactions with trigger, rules, feedback, and loop/mode definitions.
Define the design rules (Skill Laws) that all Skills must follow, including core principles such as AI-first, human-centric, and ready-to-use. When to use: When users create a new Skill, optimize an existing Skill, ask about Skill design specifications, or need to evaluate Skill quality.
Use this skill when implementing logging, metrics, distributed tracing, alerting, or defining SLOs. Triggers on structured logging, Prometheus, Grafana, OpenTelemetry, Datadog, distributed tracing, error tracking, dashboards, alert fatigue, SLIs, SLOs, error budgets, and any task requiring system observability or monitoring setup.
Autonomous iterative experimentation loop for any programming task. Guides the user through defining goals, measurable metrics, and scope constraints, then runs an autonomous loop of code changes, testing, measuring, and keeping/discarding results. Inspired by Karpathy's autoresearch. USE FOR: autonomous improvement, iterative optimization, experiment loop, auto research, performance tuning, automated experimentation, hill climbing, try things automatically, optimize code, run experiments, autonomous coding loop. DO NOT USE FOR: one-shot tasks, simple bug fixes, code review, or tasks without a measurable metric.
Guide users on how to customize Trae Skills configurations, including overriding role settings, adjusting technical preferences, and defining global rules.
Use when defining stopping rules for projects, avoiding sunk cost fallacy, setting objective exit criteria, deciding whether to continue/pivot/kill initiatives, or when users mention kill criteria, exit ramps, stopping rules, go/no-go decisions, project termination, sunk costs, or need disciplined decision-making about when to quit.
Guide a user through Stanford Biodesign's needs-finding process to define, scope, and refine a rigorous health-app need statement without jumping prematurely to solutions.
Go error handling patterns: wrapping with context, sentinel errors, custom error types, errors.Is/As chains, and HTTP error mapping. Use when implementing error returns, defining package-level errors, creating custom error types, wrapping errors with fmt.Errorf, or checking errors with errors.Is/As. Use for "error handling", "fmt.Errorf", "errors.Is", "errors.As", "sentinel error", "custom error", or "%w". Do NOT use for general Go development, debugging runtime panics, or logging strategy.
OKR trees, KPI dashboards, North Star Metric, leading/lagging indicators, and experiment design. Use when setting team goals, defining success metrics, building measurement frameworks, or designing A/B experiment guardrails.
Guides the creation of agile user stories and Gherkin feature files. Use when the user wants to create a user story, write acceptance criteria, define Gherkin scenarios, or author BDD feature files. Part of the skills-for-java project