Analyze collaboration patterns (HOW) and compute metrics from captured sessions. Use when reviewing collaboration quality, analyzing human-AI interaction, computing session metrics. Triggers include "retrospect collab", "collaboration analysis", "session patterns", "how am I collaborating".

Use when the goal is to demo the end-to-end Tessl workflow quickly and reliably. Always ask which workspace to publish to, create a minimal SKILL.md with valid frontmatter, create exactly one simple eval scenario in the expected Tessl format, run skill review on the skill directory, optionally apply one optimization pass, and use publish to trigger evals. Good triggers include "make a demo skill", "scaffold a Tessl skill", "generate one eval scenario", and "show the Tessl flow end to end".

Generate HTML presentations as self-contained single files with persistent sidebar navigation, scrollable sections, and interactive components. Use this skill when the user wants a polished visual presentation viewable in a browser. Ideal for internal decks, workshop materials, strategy frameworks, and any deliverable that should feel like a premium consulting product — not a generic AI output. Supports Metis branding (default) and client brand extraction from PPTX templates. Triggers on "html slides," "html presentation," "browser deck," or when the user explicitly asks for HTML output instead of PPTX.

Control Slack via CDP or headless API tokens. Navigate channels, read/send messages, search conversations, check unreads, and manage status. Two modes: CDP (Slack desktop with --remote-debugging-port) for full UI control, or headless (xoxp/xoxb token) for data operations without Slack running. Triggers on: slack, read slack, search slack, slack unreads, send slack message, slack status, navigate slack, check slack, slack messages, go to channel, slack DM.

Record your screen to video from Claude Code. Guided capture setup: pick a display, window, or screen region, then start/stop recording on demand. Uses ffmpeg — cross-platform (macOS, Linux, Windows). Produces MP4 with sensible defaults. Pairs with demo-narrate for voice-over. Triggers on: screencast, record screen, screen recording, capture screen, record window, record region, start recording, screen capture video.

Generate production-quality colorful icon sets using Google Imagen 4. Use this skill when the user needs custom app icons, emoji-style icons, cartoon icons, or any colorful icon set. Takes a project description, suggests icons, generates 1024px PNGs via Imagen 4, removes backgrounds, downscales to all target sizes, and delivers a review gallery for iterative refinement. Trigger on: "icon set", "generate icons", "app icons", "custom icons", "colorful icons", "cartoon icons", "emoji icons", "make icons", "icon generation", "imagen icons", or any request for a set of colorful visual assets.

Use when the user wants to narrate a demo, add voice-over to a screen recording, or create AI narration for a silent video. End-to-end pipeline that extracts frames, analyzes with parallel subagents, writes a word-budgeted voice-over script, generates TTS audio per act, and merges everything back.

Address code review comments, implement suggested changes, and respond to reviewer feedback on GitHub pull requests. Use when the user pastes a GitHub PR URL, mentions PR feedback to review, asks to handle code review comments, or references review feedback on a pull request.

Handles git and GitHub operations using the gh CLI. Use when the user asks about pull requests (PRs), GitHub issues, repo management, branching, merging, rebasing, cherry-picking, merge conflict resolution, commit history cleanup, pre-commit hook debugging, GitHub Actions workflows, or releases. Covers creating and reviewing PRs, watching CI checks, interactive rebasing, branch cleanup, submodule management, and repository archaeology with git log/blame/bisect.

Debugs native module crashes, optimizes V8 performance, configures node-gyp builds, writes N-API/node-addon-api bindings, and diagnoses libuv event loop issues in Node.js. Use when working with C++ addons, native modules, binding.gyp, node-gyp errors, segfaults, memory leaks in native code, V8 optimization/deoptimization, libuv thread pool tuning, N-API or NAN bindings, build system failures, or any Node.js internals below the JavaScript layer.

Comprehensive toolkit for generating best practice Helm charts and resources following current standards and conventions. Use this skill when creating new Helm charts, implementing Helm templates, scaffolding Chart.yaml and values.yaml, defining deployment templates, service definitions, ingress configurations, .tpl helpers, or building Helm projects from scratch. Trigger phrases include "create", "generate", "build", "scaffold" alongside terms like "kubernetes helm", "k8s charts", "helm package", "chart dependencies", "values.yaml", or "helm install".

Comprehensive toolkit for validating, linting, testing, and analyzing Helm charts and their rendered Kubernetes resources. Use this skill when working with Helm charts, validating templates, debugging chart issues, working with Custom Resource Definitions (CRDs) that require documentation lookup, or checking Helm best practices.

Generates production-ready Azure DevOps Pipelines (azure-pipelines.yml) following current best practices, security standards, and naming conventions. Use when creating or updating ADO YAML pipelines, configuring build triggers, defining multi-stage deployments, setting up template references, creating variable groups, writing release pipelines, or structuring CI/CD workflows for Azure DevOps Services or Azure DevOps Server. Handles build pipelines, YAML pipelines, Docker container builds, Kubernetes/AKS deployments, language-specific pipelines (.NET, Node.js, Python, Go, Java), and reusable step/job/stage templates. All generated configurations are validated using the devops-skills:azure-pipelines-validator skill before delivery.

Validates, lints, and security-scans Azure DevOps Pipeline configurations (azure-pipelines.yml / azure-pipelines.yaml). Use when working with ADO pipelines, YAML pipeline files, or CI/CD configurations in Azure DevOps — including validating YAML syntax and schema, detecting hardcoded secrets or credentials, checking for deprecated or unpinned task versions, enforcing best practices (caching, timeouts, display names), performing pipeline security audits, or reviewing azure-pipelines.yml before merging. Trigger terms: azure-pipelines.yml, ADO pipeline, Azure Pipelines, YAML pipeline, CI/CD validation, pipeline security scan, DevOps configuration review.

Compares project documentation against actual code implementation to identify outdated, missing, or mismatched content — then produces a prioritized report with actionable fixes. Use when the user says docs are out of date, wants to sync documentation with code, suspects the spec no longer matches implementation, notices code comments or context files are stale, or asks whether documentation reflects the current codebase. Third-person: analyzes documentation-vs-implementation alignment using JavaScript collectors, writes a structured drift report, and asks the user before applying any changes.

Compares project documentation against actual code implementation to identify outdated, missing, or mismatched content — then produces a prioritized report with actionable fixes. Use when the user says docs are out of date, wants to sync documentation with code, suspects the spec no longer matches implementation, notices code comments or context files are stale, or asks whether documentation reflects the current codebase. Third-person: analyzes documentation-vs-implementation alignment using JavaScript collectors, writes a structured drift report, and asks the user before applying any changes.

Use when user wants to update project documentation to reflect code changes, sync docs with code, refresh project context, or keep AI memory files accurate after completing an implementation task. Scans modified code, classifies the change significance, then updates or verifies Markdown context files under `context/` (overview, architecture, glossary, patterns, context-map, and domain files) so that durable AI memory stays aligned with current code truth.

Creates or updates structured SCE (Shared Context Engine) implementation plans saved to `context/plans/{plan_name}.md`. Breaks a change request into scoped, atomic tasks with clear goals, boundaries, acceptance criteria, and verification steps. Use when a user wants to plan a new feature, refactor, or integration; needs a project plan, task breakdown, implementation roadmap, or work plan; or describes a change with success criteria that requires structured planning before execution.

Reviews an existing SCE plan file (a Markdown checklist in `context/plans/`) to identify the next unchecked task, surface blockers or ambiguous acceptance criteria, and produce an explicit readiness verdict before implementation begins. Use when the user wants to continue a plan, resume work, pick the next step, or check what remains in an active plan — e.g. "continue the plan", "what's next?", "resume work on the plan", "review my plan and prepare the next task".

Use when user wants to update project documentation to reflect code changes, sync docs with code, refresh project context, or keep AI memory files accurate after completing an implementation task. Scans modified code, classifies the change significance, then updates or verifies Markdown context files under `context/` (overview, architecture, glossary, patterns, context-map, and domain files) so that durable AI memory stays aligned with current code truth.

Creates or updates structured SCE (Shared Context Engine) implementation plans saved to `context/plans/{plan_name}.md`. Breaks a change request into scoped, atomic tasks with clear goals, boundaries, acceptance criteria, and verification steps. Use when a user wants to plan a new feature, refactor, or integration; needs a project plan, task breakdown, implementation roadmap, or work plan; or describes a change with success criteria that requires structured planning before execution.

Reviews an existing SCE plan file (a Markdown checklist in `context/plans/`) to identify the next unchecked task, surface blockers or ambiguous acceptance criteria, and produce an explicit readiness verdict before implementation begins. Use when the user wants to continue a plan, resume work, pick the next step, or check what remains in an active plan — e.g. "continue the plan", "what's next?", "resume work on the plan", "review my plan and prepare the next task".