Results for “improv”

Improve code quality and maintainability through systematic identification of code smells and application of proven refactoring patterns. Use when the user requests refactoring or provides relevant inputs for this workflow.

Identify skill coverage gaps and improvement opportunities. Use when analyzing missing skills for a task, creating skill gap issues, evaluating skill effectiveness, or refining skill progressive disclosure.

Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.

Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.

Orchestrator for agent harness work — the setup that makes AI agents follow project rules and improve when they fail. FIRES PROACTIVELY when agents misbehave, repeat mistakes, ignore instructions, skip skills, or when AGENTS.md exists but docs/harness/manifest.json is missing. Also triggers on: harness engineering, agent scaffold, agent keeps failing, agent not following instructions, make agents reliable, agents going off rails, agent forgot context, improve agent setup, self-improving agents, agents keep making mistakes, why is my agent bad, agent quality, agent setup broken, agents ignore skills, same mistake again, fix agent behavior, tune agent instructions, set up agent infrastructure, after project setup agents still bad. Routes bootstrap vs evolution. Not multi-agent topology — agent-builder.

Evaluate and improve interface usability using heuristic analysis. Use when the user mentions "usability audit", "UX review", "users are confused", "heuristic evaluation", "form usability", "navigation problems", "Nielsen heuristics", "cognitive walkthrough", or "usability testing". Also trigger when reviewing a design for usability issues, improving form completion rates, or evaluating information architecture and navigation. Covers Nielsens 10 heuristics, severity ratings, and information architecture. For visual design fixes, see refactoring-ui. For conversion-focused audits, see cro-methodology.

Edit and refresh existing marketing copy through seven focused editing sweeps to improve clarity, voice, and conversion impact.

Designs, constructs, and improves offers by applying value equation analysis, bonus stacking, guarantee design, scarcity/urgency, naming, and payment structure.

Diagnose and improve MSBuild project evaluation performance by analyzing phases, glob patterns, import chains, and property functions.

Audit and improve GitHub Codespaces efficiency by analyzing devcontainer configurations, machine sizing, prebuild strategy, and idle timeout settings.

Run autonomous optimization loops that iteratively improve artifacts against evaluators using hypothesis tree refinement, without overfitting.

Evaluate and improve interface usability using heuristic analysis based on Nielsen's 10 heuristics, Krug's laws, and severity ratings.

Mines git history to compute development quality, velocity, and stability metrics, compares them against stored baselines, and tracks improvement over time.

Crops and reframes event photos to improve composition while preserving the original aspect ratio, with QA contact sheets and delivery folders.

Apply the OKRs framework to structure analysis, guide decision-making, and improve outcomes in product research and strategic planning contexts.

Writes, rewrites, or improves marketing copy for web pages, including headlines, CTAs, and page sections, with a focus on clarity, benefits, and conversion.

Builds mental toughness and adaptability through structured frameworks, daily practice routines, and reflection exercises for navigating failure, crisis, and high-pressure situations.

Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.

Safe refactor planning for Nick's codebases. Use when planning large refactors, reducing blast radius, sequencing cleanup work, or deciding how to improve messy code without breaking product velocity.

When the user wants to optimize, improve, or increase conversions on any marketing page or form — including homepage, landing pages, pricing pages, feature pages, lead capture forms, or contact form

Analyzes provided content for quality, E-E-A-T signals, and SEO best practices. Scores content and provides improvement recommendations based on established guidelines. Use PROACTIVELY for content review.

Modernizes legacy scripts (bash, Node, Python) by replacing deprecated APIs, adding error handling, converting callbacks to async/await, and improving maintainability. Turns brittle one-off scripts into reliable, documented tools.

Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.

Runs a three-phase AOI training pipeline: AutoML HPO baseline, DEFT iterative data improvement, and AutoML refinement on the augmented dataset.

Analyze landing pages and funnels to identify conversion barriers and deliver actionable, prioritized recommendations for improvement.

Improves AI skills for activation, clarity, and cross-model reliability through benchmarking, salience tuning, and regression triage.

Optimizes Dify workflows and plugins by restructuring graphs, reducing LLM token usage, tuning worker pools, and improving parallel processing.

Applies the System Usability Scale (SUS) framework to guide decision-making, structure analysis, and improve outcomes in design and user experience contexts.

Refines an existing skill in place with minimal diffs, using evidence from usage and session mining to improve triggers, workflow, metadata, and resources.

Analyzes workflows to identify inefficiencies, bottlenecks, and optimization opportunities, providing a structured report with recommendations for eliminating, resequencing, parallelizing, and automating steps.

Edit marketing copy through seven focused passes to improve clarity, voice, specificity, and emotional impact while preserving the core message.

Self-hosted observability platform for LLM applications, providing tracing, evaluation, datasets, experiments, and real-time monitoring to debug and improve AI systems.

Guided interview to Gold Code (100% AI-Readiness). Use when helping users improve their .faf file through questions. Leverages Claude Code's AskUserQuestion for seamless integration. Just type /faf-go

Patterns, conventions, and guardrails for the closed-loop systems in AegisNex. Covers the AI intelligence graph, Guardian auto-restart, multi-agent orchestration, incident lifecycle, self-improvement memory, and risk/policy gates.

Program LM pipelines with DSPy — define Signatures (input/output fields), build Modules (ChainOfThought, ReAct, Predict), compose them into Programs, then optimize with Teleprompters (BootstrapFewShot, MIPRO, COPRO) to auto-improve prompts from examples.

Generates optimized prompts for any AI tool. Use when writing, fixing, improving, or adapting a prompt for LLM, Cursor, Midjourney, image AI, video AI, coding agents, or any other AI tool.