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Found 610 Skills
Manage RFC-style specifications with validation, and dynamic generation of history, index, and namings files. Use when validating RFC documents, checking taxonomy compliance, or generating specification indices and terminology references.
Analyze a React/TypeScript component for compliance with coding guidelines and suggest improvements.
Automatically validate and fix Moodle PHP code for PSR-12 compliance with Moodle-specific exceptions (lowercase_with_underscores naming, frankenstyle prefixes). Activates when working with Moodle plugin PHP files or when code standards issues are detected.
Expert knowledge of academic writing standards for peer-reviewed papers, including citation integrity, style compliance, clarity, and scientific writing best practices. Use when reviewing or editing academic manuscripts, papers, or research documentation.
Review code for Government of Canada authentication and identity management compliance. Checks OIDC implementations, session security, scope minimization, logout handling, and RBAC integration against ITSG-33 and TBS security standards.
Validate WCAG 2.1 compliance, screen reader compatibility, and Universal Design for Learning (UDL) principles implementation throughout curriculum materials. Use when checking accessibility, validating UDL, or ensuring compliance. Activates on "accessibility check", "WCAG validation", "UDL review", or "screen reader test".
Code review skill for quality, standards compliance, and best practices
Generate synthetic training data when you don't have enough real examples. Use when you're starting from scratch with no data, need a proof of concept fast, have too few examples for optimization, can't use real customer data for privacy or compliance, need to fill gaps in edge cases, have unbalanced categories, added new categories, or changed your schema. Covers DSPy synthetic data generation, quality filtering, and bootstrapping from zero.
Find every way users can break your AI before they do. Use when you need to red-team your AI, test for jailbreaks, find prompt injection vulnerabilities, run adversarial testing, do a safety audit before launch, prove your AI is safe for compliance, stress-test guardrails, or verify your AI holds up against adversarial users. Covers automated attack generation, iterative red-teaming with DSPy, and MIPROv2-optimized adversarial testing.
Score, grade, or evaluate things using AI against a rubric. Use when grading essays, scoring code reviews, rating candidate responses, auditing support quality, evaluating compliance, building a quality rubric, running QA checks against criteria, assessing performance, rating content quality, or any task where you need numeric scores with justifications — not just categories.
Know when your AI breaks in production. Use when you need to monitor AI quality, track accuracy over time, detect model degradation, set up alerts for AI failures, log predictions, measure production quality, catch when a model provider changes behavior, build an AI monitoring dashboard, or prove your AI is still working for compliance. Covers DSPy evaluation for ongoing monitoring, prediction logging, drift detection, and alerting.
Semantic versioning guidelines for software releases. Use when assigning version numbers, deciding between major/minor/patch bumps, managing unstable (0.x.x) software versions, evaluating breaking changes, or reviewing changelogs and release notes for correct semver compliance.