Browse skills

Manage tool versions and tasks with mise (formerly rtx). Use when a user asks to manage Node.js/Python/Go versions per project, replace nvm/pyenv/asdf, or define project-level tool requirements.

Use when a startup is approached by a prospective partner and someone has to decide should we sign this partner, at what partner tier (referral / reseller / OEM / SI-consulting / strategic alliance), with what joint GTM commitment, and at what revshare. Classifies partner tier from independent-demand evidence vs. preferential-terms hunting, designs a 90-day joint GTM plan, models revshare against direct-sale margin, and surfaces kill criteria for unwinding under-performing partnerships. For Head of Partnerships, Head of BD, and Founder-CEOs doing reseller agreement, OEM deal, or strategic alliance review — not technical sale enablement, not channel cost economics, not M&A.

Inngest expert for serverless-first background jobs, event-driven workflows, and durable execution without managing queues or workers.

Use when an RFP, RFI, RFQ, security questionnaire, vendor questionnaire, or proposal request arrives and the team needs a structured response — parsing multi-section buyer-dictated requirements (MANDATORY vs WEIGHTED vs NICE-TO-HAVE), building a Shipley-method proof-point matrix mapping each requirement to a verifiable proof point, articulating 3-5 win-themes that ladder up across requirements, and producing a Shipley-derived winrate estimate that informs a bid / no-bid / partner-bid recommendation. For Bid Managers, Proposal Leads, Directors of Sales, and Sales Engineers at the response-strategy moment. Surfaces GAP requirements explicitly — never invents claims. NOT free-form proposal narrative authoring, NOT contract redline, NOT marketing collateral.

Set up a new autoresearch experiment interactively. Collects domain, target file, eval command, metric, direction, and evaluator. Use when the user runs /ar:setup or asks to start optimizing a file with the autoresearch loop.

Search for social media accounts by username across 400+ platforms using Sherlock. Use when: OSINT investigations, finding online presence by username, digital footprint analysis, brand monitoring across social platforms.

Pre-production audit that scans a codebase for security, database, deployment, code quality, AI/LLM, dependency, frontend, and observability issues. Intercepts deploy commands and blocks until critical items pass. Stack-agnostic. Use for "run ship gate", "am I ready to ship", "pre-launch audit", "can I deploy", "push to production", "go live checklist", "preflight check". Not for CI/CD setup or infra provisioning.

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.