productivity▌

Generate customizable article cover images across 5 independent dimensions and 3 aspect ratios. \n \n Combines 6 image types (hero, conceptual, typography, metaphor, scene, minimal) with 10 color palettes and 7 rendering styles for fine-grained visual control \n Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects, plus additional ratios (4:3, 3:2, 3:4) \n Auto-analyzes article content to recommend dimensions, or accepts explicit flags for type, palette, rendering, text level

Amplify safe or generic designs with intentional drama, distinctive choices, and visual confidence while maintaining usability. \n \n Systematically increases impact across typography, color, spatial composition, motion, and visual effects to create memorable experiences \n Guides away from AI design clichés (cyan gradients, glassmorphism, neon accents) toward distinctive, purposeful amplification \n Requires design context analysis first—assesses brand personality, purpose, audience, and constr

Generate original music from text prompts with customizable duration, genre, and mood control. \n \n Supports durations from 5 seconds to 10 minutes, enabling use cases from notification sounds to full cinematic scores \n Text prompts accept genre, mood, instrument, tempo, and style descriptors for fine-grained control over output \n Royalty-free music suitable for commercial use in videos, podcasts, games, ads, and presentations \n Integrates with ElevenLabs TTS and sound effects skills for com

Dispatch fresh subagents per task with two-stage review (spec compliance, then code quality) in the current session. \n \n Isolates each task to a dedicated subagent with precisely crafted context, preventing context pollution and keeping the controller focused on coordination \n Enforces a two-stage review cycle: spec compliance reviewer confirms the implementation matches requirements, then code quality reviewer checks for issues \n Handles implementer status signals (DONE, DONE_WITH_CONCERNS,

Plugins can store user-configurable settings and state in .claude/plugin-name.local.md files within the project directory. This pattern uses YAML frontmatter for structured configuration and markdown content for prompts or additional context.

Monitoring deployed machine learning models ensures they continue to perform well in production, detecting data drift, concept drift, and performance degradation.

Transform genome-wide association studies (GWAS) into actionable drug targets and repurposing opportunities.

Systematic memory management for agents through daily logging, session preservation, and knowledge extraction.

Modern file and content search.

ls -la conductor/