Results for “rev-ai”

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Detects and fixes patterns including: inflated symbolism, promotional language, superficial analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Makes AI responses feel more human by adding an inner dialogue loop that reflects on and revises the initial instinctive reply.

Generates and maintains project documentation: Google-style docstrings, README, architecture docs, and ADRs, with a mandatory post-task review gate to keep docs current.

Audits a wiki for contradictions, stale content, orphan pages, duplicates, missing sections, broken wikilinks, and AI-tell contamination, producing a lint report for human review.

Manages incidents, post-incident narratives, and organizational learning in Jeli via its REST API, covering discovery, analysis, and opportunity tracking.

Manages and analyzes Clerk authentication resources, including users, organizations, and sessions, with commands for user growth, auth health, and membership review.

AI legal document generation powered by CellCog. Contracts, NDAs, terms of service, privacy policies, freelance agreements, employment contracts, compliance reviews, legal research. Precision legal drafting from natural language prompts. Not legal advice.

Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear). Manages multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and crash-proof pipeline execution.

Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear). Manages multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and crash-proof pipeline execution.

Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear). Manages multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and crash-proof pipeline execution.

Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear). Manages multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and crash-proof pipeline execution.

Use when designing, implementing, or reviewing APIs to ensure consistent, reliable, and developer-friendly interfaces. This skill provides standardized API design principles and patterns across all companies and services.

Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear). Manages multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and crash-proof pipeline execution.

Runs a budget-aware agent-assisted engineering health audit for instruction/config drift, hooks/MCP, verifier surfaces, and AI maintainability. Use when users ask in any language to audit Claude, Codex, Pi, agent instructions, MCP or hooks, verifier coverage, or AI-maintainability drift. Not for debugging application code or reviewing PRs.

Audits all Claude skills and commands using a quality checklist and AI holistic judgment, with Quick Scan and Full Stocktake modes.

Create, update, refactor, explain, or review Semantic Kernel solutions using shared guidance plus language-specific references for .NET and Python.

Manages and analyzes Google Cloud Run services using gcloud CLI, covering service discovery, revision traffic splitting, scaling, concurrency tuning, and container diagnostics.

Use before delivering any documentation to validate quality, accuracy, and completeness. This skill provides a checklist for reviewing all documentation deliverables to ensure they meet minimum quality standards before distribution.

Create, update, refactor, explain, or review Microsoft Agent Framework solutions using shared guidance plus language-specific references for .NET and Python.

Automates hypothesis generation and testing on tabular datasets using LLMs, combining data-driven discovery with literature integration for scientific research.

Analyze any text to extract a cognitive fingerprint across 12 dimensions, revealing reasoning patterns, decision styles, and thinking signatures.

Analyzes AWS X-Ray traces and service maps, including fault and error analysis, latency investigation, sampling rule review, and group configuration.

Manage AWS cloud optimization and cost savings with nOps, including ShareSave analysis, commitment management, well-architected reviews, idle resource detection, and cost dashboards.

Use when working with API keys, credentials, tokens, certificates, or any sensitive configuration. This skill provides procedures for securely handling secrets throughout their lifecycle - from identification to storage, usage, rotation, and revocation.

Use when receiving feedback from reviews, testing, QA, or HITL processes. This skill provides a structured process for incorporating feedback into deliverables, ensuring no feedback item is lost, misunderstood, or inadequately addressed.

Use when creating, maintaining, or reviewing records of actions, decisions, changes, and events for compliance, accountability, and investigation purposes. This skill provides procedures for managing audit trails across all agent activities.

Build, review, and refactor Java backend services (Spring Boot). Use for tasks like REST API design, controllers/services/repositories, PostgreSQL persistence (JPA/MyBatis), migrations, configuration, security (Spring Security), observability, testing, performance tuning, and production hardening.

Converts syllabi, past papers, or notes into a ranked study roadmap ordered by difficulty, with support for theory, numericals, MCQs, coding, and lab prep.

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases. Credits: Original skill by @blader - https://github.com/blader/humanizer

Guides SOC 2 Type II Privacy Trust Services Criteria preparation and audit execution. Covers AICPA TSP Section 100 Privacy criteria P1-P8 including notice, choice/consent, collection, use/retention/disposal, access, disclosure, security, and quality. Includes evidence collection, control testing, and report review. Keywords: SOC 2, privacy criteria, TSP, AICPA, Type II, trust services.

Write competitive research proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC with agency-specific formatting, review criteria, budget preparation, and compliance guidance.

Prove a feature works by delegating verification to an independent sub-agent that drives the real app, then open a pull request with the proof.

Orchestrates end-to-end autonomous AI research projects using a two-loop architecture for rapid experimentation and synthesis, producing papers and presentations.

Orchestrates parallel AI agent sessions using dmux, a tmux pane manager, with patterns for research, implementation, testing, and code review across multiple harnesses.

Comprehensive guide to prevent unmaintainable code, especially from AI generation. Covers code duplication, documentation, error handling, naming conventions, architecture, performance, dependencies, modularity, testing, and technical debt prevention. Essential for code reviews and ensuring long-term code health.

A library of reusable, production-tested prompt engineering patterns for building AI-powered features. Use when designing system prompts for apps, building AI pipelines, selecting the right prompting technique for a use case, or reviewing prompts for common failure modes. Complements the prompt-engineering skill (which covers the optimization framework); this skill covers the pattern library itself.