Content & Media

Compose processing stages using a pipes-and-filters model for ETL, media processing, or compiler-like workloads. Triggers: pipeline architecture, pipes and filters, ETL, data transformation, stream processing, CI/CD pipeline, media processing, batch processing Use when: data flows through fixed sequence of transformations, stages can be independently developed and tested, parallel processing of stages is beneficial DO NOT use when: selecting from multiple paradigms - use architecture-paradigms first. DO NOT use when: data flow isn't sequential or predictable. DO NOT use when: complex branching/merging logic dominates. Consult this skill when designing data pipelines or transformation workflows.

Orchestrate tutorial generation from VHS tapes and Playwright specs to dual-tone markdown with GIF recording. Triggers: tutorial update, gif generation, tape recording, update tutorial, regenerate gifs, tutorial manifest Use when: regenerating tutorial GIFs, updating documentation demos, creating tutorials from tape files DO NOT use when: only updating text - use doc-updates. DO NOT use when: only capturing browser - use scry:browser-recording directly.

Serverless FaaS for event-driven workloads with minimal infrastructure management. Triggers: serverless, FaaS, Lambda, event-driven, pay-per-use Use when: workloads are event-driven with bursty traffic DO NOT use when: long-running processes or stateful operations required.

Evaluate public API surfaces against internal guidelines and external exemplars. Triggers: API review, API design, consistency audit, API documentation, versioning, surface inventory, exemplar research Use when: reviewing API design, auditing consistency, governing documentation, researching API exemplars DO NOT use when: architecture review - use architecture-review. DO NOT use when: implementation bugs - use bug-review. Use this skill for API surface evaluation and design review.

Combine multiple media assets (GIFs, videos) into composite tutorials. Supports vertical/horizontal layouts and sequential stitching. Triggers: combine media, stitch gifs, composite, merge recordings Use when: combining terminal and browser recordings into a single tutorial

Guide to deciding whether to escalate from a lower model (haiku/sonnet) to a higher model (sonnet/opus). Triggers: model escalation, haiku to sonnet, sonnet to opus, reasoning depth, task complexity, model selection, capability trade-off Use when: evaluating whether to escalate models, facing genuine complexity requiring deeper reasoning, novel patterns with no existing solutions, high-stakes decisions requiring capability investment DO NOT use when: thrashing without investigation - investigate root cause first. DO NOT use when: time pressure alone - urgency doesn't change task complexity. DO NOT use when: "just to be safe" - assess actual complexity instead. NEVER escalate without investigation first. This is the Iron Law.

Consolidates ephemeral LLM-generated markdown files into permanent documentation. Triggers: consolidate docs, untracked reports, ephemeral files, git cleanup, report consolidation, knowledge extraction, REPORT.md files, ANALYSIS.md files Use when: you have untracked *_REPORT.md or *_ANALYSIS.md files, git status shows markdown artifacts that shouldn't be committed, preparing PR and need to clean up working artifacts, preserving insights from code reviews DO NOT use when: files are already in docs/ or skills/ locations. DO NOT use when: files are intentionally temporary scratch notes. DO NOT use when: source files have no extractable value. Merges valuable content into permanent documentation, then deletes source files.

Code design patterns: pure functions, immutability, composition, and async. Use when designing code or functions.

Create clear, testable specifications with user stories and acceptance criteria. Triggers: spec writing, feature specification, requirements, user stories Use when: creating new specifications or writing acceptance criteria DO NOT use when: generating implementation tasks - use task-planning.

Design and construct virtual memory palaces for spatial knowledge organization using mnemonic techniques. Triggers: memory palace, spatial organization, mnemonic, knowledge architecture, domain mapping, layout design, memory structure, recall enhancement Use when: creating new memory palace structures, organizing complex domains, designing spatial layouts for knowledge retention DO NOT use when: quick knowledge search - use knowledge-locator instead. DO NOT use when: session-specific context - use session-palace-builder. Consult this skill when designing permanent memory palace structures.

Reusable patterns and templates for Claude Code skill and hook development. Triggers: validation patterns, error handling, testing templates, workflow patterns, shared patterns, reusable templates, DRY patterns, common workflows Use when: creating new skills or hooks that need consistent patterns, implementing validation logic, setting up error handling, creating test scaffolding, referencing standard workflow structures DO NOT use when: pattern is specific to one skill only. DO NOT use when: pattern is still evolving - wait for stability. DO NOT use when: pattern is context-dependent requiring variations. Reference these patterns to validate consistency across the ecosystem.

Shared testing quality metrics and standards for cross-plugin use. Referenced by pensive:test-review and parseltongue:python-testing. Triggers: testing standards, quality metrics, coverage thresholds, test quality, anti-patterns, testing best practices, quality gates Use when: evaluating test quality, setting coverage thresholds, identifying testing anti-patterns, establishing quality standards DO NOT use when: simple scripts without quality requirements. Consult this skill when establishing testing quality standards.

Build a minimal, stable core system that loads plug-ins to provide feature variability and extensibility for platform development. Triggers: microkernel, plugin architecture, plugin system, extensibility, platform design, IDE architecture, marketplace, core system, plugin loader Use when: building platforms, IDEs, or marketplaces with third-party extensions, core stability is critical while features vary, plugin isolation is needed DO NOT use when: selecting from multiple paradigms - use architecture-paradigms first. DO NOT use when: no extensibility requirements exist. DO NOT use when: plugin isolation overhead isn't justified. Consult this skill when designing plugin architectures or building platforms.

Employ the Hexagonal (Ports & Adapters) pattern to decouple domain logic from infrastructure, maximizing flexibility and testability. Triggers: hexagonal architecture, ports and adapters, infrastructure independence, dependency inversion, clean architecture, domain isolation, adapter pattern, infrastructure abstraction, database independence, framework independence Use when: designing systems with strong business logic separation, anticipating infrastructure changes, needing easy mocking for tests, building portable domain code DO NOT use when: selecting from multiple paradigms - use architecture-paradigms first. DO NOT use when: building simple CRUD apps without complex domain logic. Consult this skill when implementing hexagonal patterns or migrating to port-based design.

Design skills as modular building blocks for predictable token usage. Triggers: skill design, skill architecture, modularization, token optimization, skill structure, refactoring skills, new skill creation, skill complexity Use when: creating new skills that will be >150 lines, breaking down complex monolithic skills, planning skill architecture, refactoring overlapping skills, reviewing skill maintainability, designing skill module structure DO NOT use when: evaluating existing skill quality - use skills-eval instead. DO NOT use when: writing prose for humans - use writing-clearly-and-concisely. DO NOT use when: need improvement recommendations - use skills-eval. Use this skill BEFORE creating any new skill. Check even if unsure.

Design, manage, and evolve digital gardens as living knowledge bases within memory palaces. Triggers: digital garden, knowledge base, linking, note curation, content lifecycle, garden maintenance, bidirectional links, knowledge evolution Use when: managing note collections, creating link structures, maintaining knowledge bases, tending garden health and growth DO NOT use when: creating memory palace structures - use memory-palace-architect. DO NOT use when: evaluating new knowledge - use knowledge-intake. Consult this skill when cultivating and maintaining digital gardens.

Guide to formatting review deliverables for consistency, ensuring findings are comparable across different types of analysis. Triggers: report formatting, deliverable structure, consistent output, review output, findings format, report template, output consistency Use when: formatting final review outputs, ensuring consistent deliverable structure, making findings comparable across reviews DO NOT use when: capturing evidence during analysis - use evidence-logging. DO NOT use when: reviewing changes - use diff-analysis or review-core first. Consult this skill when formatting final review deliverables.

Gemini CLI delegation workflow implementing delegation-core for Google's Gemini models. Triggers: gemini cli, gemini delegation, google gemini, 1M context, large file analysis, gemini batch, gemini summarization, gemini extraction Use when: delegation-core selected Gemini, need Gemini's 1M+ token context window, batch processing or large document summarization required DO NOT use when: deciding which model to use - use delegation-core first. DO NOT use when: gemini CLI not installed or authenticated. Consult this skill when implementing Gemini-specific delegation workflows.

Systematically uncover and fix bugs using language-specific expertise and reproducible evidence. Triggers: bug hunting, defect detection, debugging, fix verification, bug fix, regression check, error investigation, defect documentation Use when: deep bug hunting needed, documenting defects, verifying fixes, systematic debugging required DO NOT use when: test coverage audit - use test-review instead. DO NOT use when: architecture issues - use architecture-review. Use this skill for systematic bug hunting with evidence trails.

Detect codebase bloat through progressive analysis: dead code, duplication, complexity, and documentation bloat. Triggers: bloat detection, dead code, code cleanup, duplication, redundancy, codebase health, technical debt, unused code Use when: preparing for refactoring, context usage is high, quarterly maintenance, pre-release cleanup DO NOT use when: actively developing new features, time-sensitive bug fixes. DO NOT use when: codebase is < 1000 lines (insufficient scale for bloat). Progressive 3-tier detection: quick scan → targeted analysis → deep audit.