Skills directory · page 54

Head of Product: quarterly OKRs cascaded from company to team, product vision, roadmap, team structure. Use whenever the user asks to set OKRs, a vision or roadmap, or align teams on strategy.

Create a comprehensive product strategy using the 9-section Product Strategy Canvas — vision, segments, costs, value propositions, trade-offs, metrics, growth, capabilities, and defensibility. Use when building a product strategy, creating a strategic plan, or defining product direction.

Brainstorm an inspiring, achievable, and emotional product vision that motivates teams and aligns stakeholders. Use when defining or refining a product vision, creating a vision statement, or aligning the team around a shared direction.

Local-evidence production readiness audit for shipped apps, pre-launch reviews, post-merge checks, and "what breaks in prod?" questions without sending repo data to an external audit service. Use when auditing production readiness before launch, after a merge, or when asked what breaks in prod.

Build the standalone Forge artifact with strict routing inputs and confirm its static output exists.

Autonomously deep-scan entire codebase line-by-line, understand architecture and patterns, then systematically transform it to production-grade, corporate-level professional quality with optimizations

Codified expertise for production scheduling, job sequencing, line balancing, changeover optimization, and bottleneck resolution in discrete and batch manufacturing. Informed by production schedulers with 15+ years experience. Includes TOC/drum-buffer-rope, SMED, OEE analysis, disruption response frameworks, and ERP/MES interaction patterns. Use when scheduling production, resolving bottlenecks, optimizing changeovers, responding to disruptions, or balancing manufacturing lines.

Codified expertise for production scheduling, job sequencing, line balancing, changeover optimization, and bottleneck resolution in discrete and batch manufacturing. Based on the knowledge of production schedulers with 15+ years of experience. Includes theory of constraints/drum-buffer-rope, quick changeover, overall equipment effectiveness analysis, disruption response frameworks, and enterprise resource planning/manufacturing execution system interaction patterns. Use when scheduling production, resolving bottlenecks, optimizing changeovers, responding to disruptions, or balancing manufacturing lines.

Guide technical communication for software developers. Covers email structure, team messaging etiquette, meeting agendas, and adapting messages for technical vs non-technical audiences. Use when drafting professional messages, preparing meeting communications, or improving written communication.

When the user wants to create SEO-driven pages at scale using templates and data. Also use when the user mentions "programmatic SEO," "template pages," "pages at scale," "directory pages," "location pages," "[keyword] + [city] pages," "comparison pages," "integration pages," or "building many pages for SEO." For auditing existing SEO issues, see seo-audit.

Use when building many SEO pages from a template and data (location, integration, comparison or directory pages), before generating them. Designs URL patterns with url_pattern_generator.py and guards against thin-content penalties.

Build Progressive Web Apps (PWAs) with offline support, installability, and caching strategies. Trigger whenever the user mentions PWA, service workers, web app manifests, Workbox, 'add to home screen', or wants their web app to work offline, feel native, or be installable.

Build and maintain a three-layer project awareness system that gives Claude Code both the 30,000-foot architectural view AND the ability to drill into specifics — without exceeding context limits. Use this skill whenever: starting work on any project with 10+ source files; the user says "bootstrap", "set up awareness", "analyze this project", "build the map"; the user says "you're missing the big picture", "you don't understand the architecture", "you keep forgetting", "update the docs"; a CLAUDE.md exists with an [AWARENESS] section (this means the system is already bootstrapped — load and follow it); or when starting an Agent Teams session on any project (each agent must load its subsystem doc). This skill supersedes and works alongside deep-focus. Deep-focus is HOW you work carefully; project-awareness is HOW the project's knowledge is organized and maintained.

Operate execution flow across GitHub and Linear by triaging issues and pull requests, linking active work, and keeping GitHub public-facing while Linear remains the internal execution layer. Use when the user wants backlog control, PR triage, or GitHub-to-Linear coordination.

Coordinate execution flow between GitHub and Linear by triaging issues and pull requests, linking active work, and keeping GitHub externally visible while Linear serves as the internal execution layer. Use when the user needs backlog control, PR triage, or GitHub–Linear coordination.

Project-specific skill template covering architecture, patterns, testing, and deployment guidance.

Project-specific skill template covering architecture, patterns, testing, and deployment guidance.

Complete guide to Prometheus setup, metric collection, scrape configuration, and recording rules.

Graduate a proven pattern from auto-memory (MEMORY.md) to CLAUDE.md or .claude/rules/ for permanent enforcement. Use when the user runs /si:promote or asks to make a learned behavior permanent.

Caching strategies for LLM prompts including Anthropic prompt caching, response caching, and CAG (Cache Augmented Generation) Use when: prompt caching, cache prompt, response cache, cag, cache augmented.

Optimize LLM prompt caching hit rate to reduce API costs and improve latency. Analyzes prompt structure, identifies cacheable vs non-cacheable content, and recommends restructuring to maximize cache reuse. TRIGGER when: user says "prompt cache", "cache hit rate", "reduce LLM cost", "optimize token usage", "cheaper LLM calls", or asks about prompt caching strategies for OpenAI/Anthropic/other providers. DO NOT TRIGGER when: user just wants to optimize a single prompt's quality (use prompt-optimizer instead), or asks about general caching infrastructure.

Expert in designing effective prompts for LLM-powered applications. Masters prompt structure, context management, output formatting, and prompt evaluation. Use when: prompt engineering, system prompt, few-shot, chain of thought, prompt design.

Use when a marketing team's AI prompts need testing, versioning or governance, before shipping a prompt. A/B tests prompts against cases with prompt_tester.py and keeps diffed versions with prompt_versioner.py.

Expert guide on prompt engineering patterns, best practices, and optimization techniques. Use when user wants to improve prompts, learn prompting strategies, or debug agent behavior.

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework

Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library

Guarantee valid JSON/XML/code structure during generation, use Pydantic models for type-safe outputs, support local models (Transformers, vLLM), and maximize inference speed with Outlines - dottxt.ai's structured generation library

Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability.

Use when prompts run in production and need versioning, a registry, A/B tests, regression checks or an eval pipeline. Sets up the release process for prompts; single-prompt quality: senior-prompt-engineer.

Curated collection of high-quality prompts for various use cases. Includes role-based prompts, task-specific templates, and prompt refinement techniques. Use when user needs prompt templates, role-play prompts, or ready-to-use prompt examples for coding, writing, analysis, or creative tasks.

Analyze the original prompt, identify intent and gaps, match ECC components (skills/commands/agents/hooks), and return an optimized prompt ready to paste. Advisory only: never execute the task itself. Trigger when the user asks to optimize or improve a prompt, asks how to write one, requests help refining an instruction, or explicitly requests better prompt quality. Equivalent Chinese phrases also trigger: “优化prompt”, “改进prompt”, “怎么写prompt”, and “帮我优化这个指令”. Do not trigger when the user wants direct task execution or says “直接做” (just do it). Do not trigger for “优化代码”, “优化性能”, “optimize performance”, or “optimize this code”: these are refactoring/performance tasks rather than prompt optimization.

Analyze draft prompts, detect intent and missing context, match ECC commands, skills, and agents, and output a ready-to-paste optimized prompt with diagnosis and rationale — advisory only, never executes the task. Use when the user says 'optimize prompt', 'improve my prompt', 'rewrite this prompt', 'help me prompt', 优化prompt, 改进prompt, 怎么写prompt, or 帮我优化这个指令; not for requests to optimize code or performance.

Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.

Build a throwaway prototype to answer a design question. Use when the user wants to sanity-check whether a state model or logic feels right, or explore what a UI should look like.

Use when investigating a root-cause claim for a past failure; checking a claim that a reported failure cannot be reproduced; reviewing a PR, diff, proposal or contract for concrete defects; verifying a live status or metric before reporting it; verifying an Android license-tester purchase; verifying time-windowed usage or billing queries; reconciling conflicting readings; judging parse or validation failures after a truncated or bounded read; or checking that a resource or bug is absent. Use deliver-and-verify to publish or arm a PR. Use unblock to restore currently failing work and challenge to compare designs. Full-read parse errors need no truncation investigation. Static general knowledge, arithmetic and routine acknowledgements do not need this skill.

Query PubChem via PUG-REST API/PubChemPy (110M+ compounds). Search by name/CID/SMILES, retrieve properties, similarity/substructure searches, bioactivity, for cheminformatics.

Confirm the live Skillz Forge GitHub Pages site matches the last successful deploy run, independent of whether the last deploy-pages.yml run happened to report success.

Confirm the published Skillz Forge review surface still preserves failed-contract keyboard recovery after a GitHub Pages deploy.

Verify GitHub Pages publishing remains family-agnostic and fail-closed.

Direct REST API access to PubMed. Advanced Boolean/MeSH queries, E-utilities API, batch processing, citation management. For Python workflows, prefer biopython (Bio.Entrez). Use this for direct HTTP/REST work or custom API implementations.

Measure local AI task latency, token usage, errors and verified outcomes using Pudu AI hardware evidence and installed Ollama models. Use when comparing local task runs, choosing a local model for a bounded subtask, or recording reproducible task telemetry.

This skill should be used when working with reinforcement learning tasks including high-performance RL training, custom environment development, vectorized parallel simulation, multi-agent systems, or integration with existing RL environments (Gymnasium, PettingZoo, Atari, Procgen, etc.). Use this skill for implementing PPO training, creating PufferEnv environments, optimizing RL performance, or developing policies with CNNs/LSTMs.

Use for what people are saying right now about a topic (trends, sentiment, complaints, tool comparisons) across Reddit, Hacker News and the web in a recent window. Returns a cited briefing with engagement signals.

Use when setting up Playwright in a project ('set up playwright', 'add e2e tests', 'configure playwright', 'init playwright').

Use when reviewing Playwright tests for quality ('review tests', 'audit tests', 'playwright best practices check').

Build production-ready AI agents with PydanticAI — type-safe tool use, structured outputs, dependency injection, and multi-model support.

Create Pydantic models following the multi-model pattern with Base, Create, Update, Response, and InDB variants. Use when defining API request/response schemas, database models, or data validation in Python applications using Pydantic v2.

Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.

Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.