Browse skills

Frontend-engineering orchestrator. Walks the 7 Matt Pocock forcing questions (device, LCP target, rendering, bundle budget, SEO vs auth, design system, WCAG), picks the framework/rendering profile, forks into specialists (a11y-audit, performance-profiler, epic-design, apple-hig-expert, playwright-pro) rather than reimplementing their scope. Forks own context. Invoke via /cs:frontend-review or Agent({subagent_type:"cs-frontend-engineer",...}).

Fullstack-engineering orchestrator. Walks the Matt Pocock 7-question forcing-question grill, runs the deterministic profile picker, then forks into the POWERFUL-tier specialists (api-design-reviewer, database-designer, slo-architect, ci-cd-pipeline-builder, performance-profiler) rather than reimplementing their scope. Forks own context so heavy ingestion does not pollute parent thread. Invoke via /cs:fullstack-review or Agent({subagent_type:"cs-fullstack-engineer",...}).

Operate Sequenzy email marketing from an AI agent. Use when a user asks to manage SaaS email campaigns, subscribers, lists, segments, templates, lifecycle sequences, transactional email, delivery stats, or AI-generated email copy with Sequenzy. Prefer the Sequenzy CLI or API, inspect before mutation, and surface dashboard review URLs for created campaigns or sequences.

Provides Xquik-backed X/Twitter workflows for Hermes Agent through Hermes Tweet. Use when tasks mention searching tweets, reading tweet replies, looking up users, exporting followers, monitoring tweets, posting tweets or replies, sending DMs, Xquik Twitter automation, or approval-gated Twitter actions.

Use when running an annual SaaS audit, doing category-level spend review, or rationalizing the supplier base — when the user needs a spend audit, spend categorization (UNSPSC-aligned with Pareto breakdown and industry profiles), purchasing-cycle analysis (bottleneck categories per Goldratt's Theory of Constraints), or risk-balanced supplier consolidation that refuses single-source recommendations for tier-1 categories without a documented break-glass plan. Triggers on "spend audit", "SaaS audit", "spend categorization", "supplier rationalization", "supplier consolidation", "category strategy", "duplicate SaaS", "renewal cluster".

Use when converting a PDF into another format such as Markdown, HTML, text, JSON, DOCX, or structured notes and the agent must choose the best extraction route, settings, and cleanup strategy for maximum fidelity and readability.

Interpret third-party feedback by running parallel internal and peer interpretations to surface intent, correctness concerns, and ambiguities. Use when the user asks to "interpret feedback", "interpret comments", "what does this feedback mean", "clarify reviewer intent", "understand this review", or "interpret these suggestions".

Explicitly save important knowledge to auto-memory with timestamp and context. Use when a discovery is too important to rely on auto-capture.

Generate walkthrough videos from Stitch projects using Remotion with smooth transitions, zooming, and text overlays

Generate test report. Use when user says "test report", "results summary", "test status", "show results", "test dashboard", or "how did tests go".

Automation discovery audit skill. Walks through a 5-question workflow intake, then audits Gmail/Calendar/Slack/task trackers to identify automation opportunities. Use when a user wants to discover what processes in their business can be automated.

Configure and optimize .geminiignore files for AI context window efficiency and token cost reduction (FinOps).

Deterministic search across arXiv, PubMed/PMC, and US policy corpora with daily freshness cutoffs.

Self-hosted semantic memory for AI agents via MCP. Save worklogs, decisions, and notes, then recall them across sessions by meaning, not keyword. Postgres + pgvector with auto-tagging.

Agent-first social media publishing skill — schedule and publish posts across 13 platforms (X, LinkedIn, Instagram, Facebook Pages, TikTok, Discord, Telegram, YouTube, Reddit, WordPress, Pinterest) via a single workspace API key.

Stand up the project's live app and hand it to the user to try a change firsthand, then gate on their verdict before continuing. Use when the user asks to "preview the change", "let me try it", "spin up the app so I can test it", "set it up so I can poke at it", or before finalizing a UI/UX change that needs human eyes.

Implement efficient similarity search with vector databases. Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance.

Correctness-first: forces writing the function contract, loop invariant, termination argument, and edge cases BEFORE code. Catches Boyer-Moore, leftmost binary search, QuickSelect traps.

Algorithm-first discipline: state Big-O, data structure, and algorithm family BEFORE writing loops, queries, or recursion. Catches O(n^2), N+1, and brute-force defaults.

Math-heavy escalation for n >= 10^6 — Bloom, HyperLogLog, Count-Min, MinHash/LSH, FFT, JL projection, sweep line. Use when classical O(n log n) is the floor and approximate or math wins.