Skill UI

A disciplined approach for red teaming and security assessments, emphasizing scope authorization, impact verification, and data minimization. Ensures thorough coverage without over-extraction or premature stopping during authorized engagements.

A critical discipline for managing expenses when integrating paid AI or inference APIs. This guard treats dollar cost as a third complexity dimension, mandating the definition of cost contracts (max calls per run, max budget per run, max budget per day). It enforces best practices for bounding loops, retries, and fan-out, ensuring that code bugs cannot lead to unexpected overspending. Best practice requires configuring hard caps both in the code and at the provider dashboard for defense in depth.

A two-layer skill combining disciplined coding practices with terse prose output. The THINK layer enforces surgical edits, simplicity, and goal-driven execution before writing code. The SPEAK layer compresses responses into 'caveman' style for token efficiency, removing filler words while preserving technical accuracy. Ideal for requests requiring brevity, token efficiency, or rigorous engineering discipline.

Expert TDD orchestrator for enforcing red-green-refactor discipline, coordinating multi-agent workflows, and applying modern test-driven development practices across software projects. Covers test suite architecture, AI-assisted test generation, metrics, and framework integration.

Execute a comprehensive Test-Driven Development (TDD) workflow enforcing the red-green-refactor discipline. This skill guides test-first development through coordinated agent orchestration, covering requirements analysis, unit test creation, implementation, refactoring, and integration testing with strict coverage thresholds.

This skill serves as a trading journal integrated with Notion, capturing the decision process rather than just trade fills. It records thesis, plan, and emotions at entry, then reviews decision quality against the original plan instead of P&L. It manages trade logs, confirms details, and grades execution to improve trading discipline.

WGM is a robust, agentic methodology designed to transform vague or rough requirements into working, validated software. It enforces a disciplined workflow across six stages: deep alignment (Grill), structured planning, deterministic iterative building (Loop), mandatory holdout-scenario judging, and final documentation audits. It ensures that the resulting code converges against rigorously tested acceptance criteria rather than relying on single-pass generation.

A critical skill for reviewing WooCommerce extensions, payment integrations, and checkout logic before deployment. Ensures code follows security standards, HPOS compatibility, proper data handling, and runtime discipline to prevent systematic AI failures.

This skill enforces rigorous governance and discipline when AI modifies systems, debugs code, or makes root-cause claims. It mandates safety gates (e.g., backup, blast radius check), demands evidence for every diagnosis, and prevents common AI shortcuts like guessing or deflecting. Use this for critical code modifications, complex debugging, and high-stakes deployments to ensure thoroughness and safety.

Design and revise dashboards that people trust and can read at a glance: comment etiquette, visual hierarchy, KPI layout, data-ink discipline, colour, labelling and chart choice, following Stephen Few and Edward Tufte.

A disciplined approach for diagnosing hard bugs and performance regressions. This skill guides users to build tight feedback loops, reproduce issues, and minimize scenarios before hypothesizing. It emphasizes redacting secrets, creating deterministic tests, and avoiding premature assumptions. Use when debugging complex failures or performance issues in software development.