agent-skills-standard

Enforce "No Exploit, No Report" policy with PoC construction standards, false-positive filtering, and evidence collection per vulnerability class across backend, frontend, and mobile. Use when validating security findings, constructing exploit proofs, filtering false positives, or writing pentest findings.

Judge and shape UI/UX for products used by parents and young children - audience fit, accessibility, safety and trust, comfort, consistency, and human feel. Use when reviewing or designing family, parenting, or kids app screens on phone or tablet.

Pre-write audit for skill violations: checks planned code against loaded skill anti-patterns before any file write. Use when writing Flutter/Dart/TS code or editing SKILL.md files with active project skills. Load as composite; on auto-fixed violation, also load +common/common-learning-log.

Pre-write audit for skill violations: checks planned code against loaded skill anti-patterns before any file write. Use when writing Flutter/Dart/TS code or editing SKILL.md files with active project skills. Load as composite; on auto-fixed violation, also load +common/common-learning-log.

Enforce version control best practices for commits, branching, pull requests, and repository security. Use when writing commits, creating branches, merging, or opening pull requests.

Enforce version control best practices for commits, branching, pull requests, and repository security. Use when writing commits, creating branches, merging, or opening pull requests.

Append a learning entry to AGENTS_LEARNING.md when an AI agent makes a mistake. Auto-activates after a pre-write audit auto-fix, a retrospective correction loop, or a mid-session user correction. Use when: mistake, wrong, correction, my bad, agent error, learning log.

Append a learning entry to AGENTS_LEARNING.md when an AI agent makes a mistake. Auto-activates after a pre-write audit auto-fix, a retrospective correction loop, or a mid-session user correction. Use when: mistake, wrong, correction, my bad, agent error, learning log.

OWASP LLM Top 10 (2025) audit checklist for AI applications, agent tools, RAG pipelines, and prompt construction. Use when performing any security review touching LLM client code, prompt templates, agent tools, or vector stores.

OWASP LLM Top 10 (2025) audit checklist for AI applications, agent tools, RAG pipelines, and prompt construction. Use when performing any security review touching LLM client code, prompt templates, agent tools, or vector stores.

Apply motion design principles for mobile apps covering timing curves, transitions, gestures, and performance-conscious animations. Use when implementing screen transitions, gesture-driven interactions, shared-element animations, or optimizing animation frame rates on iOS, Android, or Flutter.

Enforce universal mobile UX principles for touch-first interfaces including touch targets, safe areas, and mobile-specific interaction patterns. Use when building mobile screens, handling touch interactions, or validating safe area compliance.

Standardizes mobile UI audits, performance/scroll checks, RTL verification, and state-specific testing on iOS/Android.

Enforce structured JSON logging, OpenTelemetry distributed tracing, and RED metrics across backend services. Use when adding request correlation, setting up tracing spans, defining SLO burn-rate alerts, or instrumenting middleware.

Infer the requesting operator's technical fluency from message content (never ask directly) and adapt register — business, hybrid, or technical — across SDLC workflow output. Use when starting sdlc, brainstorm-feature, plan-feature, verify-work, publish-notes, or session-report, or whenever a request's phrasing signals a non-technical or cross-stack operator.

OWASP Top 10 audit checklists for Web Applications (2021), APIs (2023), and Mobile (2024). Use when performing any security review, PR review, or codebase audit touching web, mobile, or API code.

OWASP Top 10 audit checklists for Web Applications (2021), APIs (2023), and Mobile (2024). Use when performing any security review, PR review, or codebase audit touching web, mobile, or API code.

PTES-aligned penetration testing methodology for backend, frontend, and mobile. Provides attack taxonomy, exploit techniques per vulnerability class, and platform-specific test matrices. Use when executing pentest workflow, planning security assessments, mapping attack surfaces, or building threat models.

Enforce universal standards for high-performance development. Use when profiling bottlenecks, reducing latency, fixing memory leaks, improving throughput, or optimizing algorithm complexity in any language.

Enforce universal standards for high-performance development. Use when profiling bottlenecks, reducing latency, fixing memory leaks, improving throughput, or optimizing algorithm complexity in any language.