Results for “how-to”

Turn "can we even hit this number" into a capacity model that shows the truth before the quarter does. Models ramped-rep productivity, builds the hiring plan the target requires, states the ramp assumptions plainly, and names the gap between plan and capacity so nobody discovers it in month three. Built for B2B sales and RevOps leaders, customizable to your ramp and your CRM. Trigger on "build a capacity model", "how many reps to hit the number", "what's the hiring plan", "are we capacity constrained", "model the ramp", or any capacity or headcount planning question.

Flip a problem, goal, or decision 180 degrees to find what forward thinking misses. Asks what would guarantee failure, then works backward to what must be avoided or changed. Load when the user says "invert this", "flip this problem", "what would guarantee failure", "think backward", "reverse engineer the goal", "think about it backwards", or when deep-thinking diagnoses an inversion frame. Also triggers on "what's the opposite of success here", "how would we sabotage this". Two methods: Failure Inversion and Opposite Goal. Max 2 clarifying questions before inverting. Always returns forward actions. For broader analysis, deep-thinking calls this.

Analyze raw prompts, identify intent and gaps, match ECC components (skills/commands/agents/hooks), and output a ready-to-paste optimized prompt. Advisory role only — never executes the task itself. TRIGGER when: user says "optimize prompt", "improve my prompt", "how to write a prompt for", "help me prompt", "rewrite this prompt", or explicitly asks to enhance prompt quality. Also triggers on Chinese equivalents: "优化prompt", "改进prompt", "怎么写prompt", "帮我优化这个指令". DO NOT TRIGGER when: user wants the task executed directly, or says "just do it" / "直接做". DO NOT TRIGGER when user says "优化代码", "优化性能", "optimize performance", "optimize this code" — those are refactoring/performance tasks, not prompt optimization.

Turn "we should get press" into an earned-media plan a journalist might actually answer. The story angle worth their byline, a target list by beat, a pitch built for one reporter at a time, and a follow-up rhythm that is persistent without being a pest. Built for B2B teams doing their own PR, customizable to your story and your beats. Trigger on "help me pitch this", "build a PR plan", "which journalists cover this", "write a media pitch", "how do I follow up with press", or any earned-media outreach question.

Turn a pipeline target into a demand-generation plan that actually maps to the number. The ICP worth spending on, the offers by funnel stage, the channel mix that reaches them, the content that earns attention, and the pipeline math worked backward from the goal so you know if the plan can even hit it. Built for B2B marketing teams, customizable to your funnel and your channels. Trigger on "build a demand gen plan", "how do we hit our pipeline number", "what's our channel mix", "plan our content", "work the funnel math backward", or any demand-generation planning question.

Firm-fixed-price cost buildup mirroring 1102 IGCE FFP wrap-rate math (BLS OEWS + GSA CALC+ + GSA Per Diem). USE WHEN the user asks to "build an FFP IGCE", "wrap rate buildup", "FFP cost estimate", "layer fringe overhead G&A fee", "how should we price this FFP task order", or "IGCE parity for our bid". Pulls labor categories from pursuit vault or defaults, stacks fringe/overhead/G&A/fee, exports JSON + XLSX to Studio. DO NOT USE FOR T&M/LH pricing (`igce-builder-lh-tm`), cost-reimbursement (`igce-builder-cr`), OT milestones (`ot-prototype-strategist`), or obligation intel (`competitive-intel`).

Profiles 5 competitors, identifies white space, and delivers a positioning recommendation — not a feature comparison table. Use this skill — proactively and without waiting to be asked — whenever entering a new market, before defining bets in product strategy, when pricing needs a competitive anchor, or when losing deals to a specific competitor. Also triggers for: "competitive analysis", "competitor research", "who are my competitors", "market landscape", "white space", "differentiation angle", "competitive positioning", "market entry risk", "losing to X", "pricing strategy", "threat assessment", "who owns this segment", "competitive brief", "how do we differentiate", "what are competitors doing". Produces a decision-ready competitive map: 5 competitor profiles, white space analysis, and a Where-to-Win recommendation with explicit areas to ignore.

Turn a target account list into a real account-based play, not a spray. It tiers the accounts, sets the research angle per tier, builds the multi-thread across marketing and sales, and orchestrates the touches so the account feels one coordinated motion instead of a rep and a marketer working past each other. Built for B2B revenue teams, customizable to your CRM and your channels. Trigger on "build an ABM play", "account-based plan for this list", "how do I run ABM on these accounts", "tier my target list", "coordinate marketing and sales on these accounts", or any account-based planning request.

Evidence-based investigation of issues, bugs, API calls, integrations, and other aspects of software development that need a deep dive to find the root cause and solutions. Use when you need to debug, troubleshoot, diagnose, or figure out why something is broken. Does not review code for quality or style — use code-review for auditing changes or post-code-review-to-pr for posting review feedback to GitHub. Does not assess architectural health or structural risk — use architectural-analysis for architectural concerns. Does not research open-ended options, prior art, or how something works when nothing is broken — use research for that. Does not capture feedback on Han's own skills — use han-feedback for that.

Relight a still image — change the lighting setup, color temperature, direction, or mood — on RunComfy via the `runcomfy` CLI. Routes to Qwen Edit 2509's dedicated `relight` LoRA endpoint for purpose-built relighting, with fallback to identity-preserving edit endpoints (Nano Banana 2 Edit, GPT Image 2 Edit, FLUX Kontext Pro) when prose lighting language is enough. Use for product relighting (studio softbox → window light), portrait mood shift (overcast → golden hour), or color-grade change. Triggers on "relight", "relighting", "change the lighting", "make it golden hour", "studio lighting", "rim light", "blue hour", "soft window light", "change light direction", "color temperature", or any explicit ask to alter how a still is lit.

Relight a still image — change the lighting setup, color temperature, direction, or mood — on RunComfy via the `runcomfy` CLI. Routes to Qwen Edit 2509's dedicated `relight` LoRA endpoint for purpose-built relighting, with fallback to identity-preserving edit endpoints (Nano Banana 2 Edit, GPT Image 2 Edit, FLUX Kontext Pro) when prose lighting language is enough. Use for product relighting (studio softbox → window light), portrait mood shift (overcast → golden hour), or color-grade change. Triggers on "relight", "relighting", "change the lighting", "make it golden hour", "studio lighting", "rim light", "blue hour", "soft window light", "change light direction", "color temperature", or any explicit ask to alter how a still is lit.

Relight a still image — change the lighting setup, color temperature, direction, or mood — on RunComfy via the `runcomfy` CLI. Routes to Qwen Edit 2509's dedicated `relight` LoRA endpoint for purpose-built relighting, with fallback to identity-preserving edit endpoints (Nano Banana 2 Edit, GPT Image 2 Edit, FLUX Kontext Pro) when prose lighting language is enough. Use for product relighting (studio softbox → window light), portrait mood shift (overcast → golden hour), or color-grade change. Triggers on "relight", "relighting", "change the lighting", "make it golden hour", "studio lighting", "rim light", "blue hour", "soft window light", "change light direction", "color temperature", or any explicit ask to alter how a still is lit.

Design decisions for when and what sounds to use in web apps, mobile apps, and desktop native apps — plus how to create them with AI. Covers UI sound vocabulary (confirms, alerts, transitions, errors), platform conventions (iOS, macOS, Material), creating sounds with AI tools (ElevenLabs, AudioCraft, Stable Audio), Web Audio API for procedural sounds, haptic-audio pairing, and the psychology of satisfying vs. annoying UI sounds. Activate on 'app sounds', 'UI sounds', 'notification sound', 'sound design app', 'earcons', 'sonic branding', 'interaction sounds', 'feedback sounds', 'app audio', 'satisfying sounds'. NOT for professional audio engineering (use sound-engineer), Windows 3.1 retro sounds specifically (use win31-audio-design), music composition (use sound-engineer).

When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program," or "experiment playbook." Use this whenever someone is comparing two approaches and wants to measure which performs better, or when they want to build a systematic experimentation practice. For tracking implementation, see analytics. For page-level conversion optimization, see cro.

Evaluate any project, product, or system's claims against its actual implementation — scoring each claim for truth, identifying architectural gaps, assessing competitive positioning, proposing creative solutions, and producing an actionable roadmap. Load when the user asks to evaluate claims, reality-check a project, assess what this project actually does vs what it says, validate product claims, or score a system's credibility. Also triggers on "is this real", "does this work as claimed", "evaluate this project", "assess the gap between claims and reality", "how credible is this", "investor assessment", "score these claims", or "what's real vs marketing".

When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' or 'optimize for Claude/Gemini.' Use this whenever someone wants their content to be cited or surfaced by AI assistants and AI search engines. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema-markup.

Score any piece of writing for AI-generation tells and produce a weighted 0-100 scorecard with flagged evidence and ranked fixes. Use this skill whenever the user asks "does this sound AI-written", "run this through the AI detector", "score this writing", "check this for AI tells", "would this pass as human", "humanize check", or wants any article, blog post, email, or copy audited for AI patterns before publishing. Also use it when the user pastes or points to text and asks how it reads, whether it's too "ChatGPT-ish", or wants a QA pass on generated content. Works on pasted text, files, and URLs.

Strip a problem to its irreducible fundamental truths and rebuild the solution from the ground up — free from analogy, convention, and inherited assumptions. Load when the user feels constrained by how something has always been done, when existing solutions feel expensive or inefficient for no good reason, when the user asks to think from first principles, challenge the fundamentals, or rebuild this from scratch. Also triggers on "why does it have to work this way", "what are the actual constraints here", "ignore what everyone else does", or when deep-thinking diagnoses a convention-break frame. Based on Aristotle's first principles method, popularised by Musk and Feynman. Produces genuinely novel solutions by eliminating convention.

Decide, before an expensive workflow runs, whether an artifact needs a full rebuild, a partial refresh, a skip, or a recycle. Inspects how old the artifact is and what actually changed underneath it, then returns a section-by-section plan with the token and cost savings. The cheap gate that keeps expensive generation from running on data that did not move. Built for anyone running repeatable AI workflows, customizable to your artifacts and your data sources. Trigger on "should we regenerate this", "refresh the report", "is this still fresh", "what needs updating", "when was this last run", "do we have a fresh brief", or any artifact-refresh question.

Query cBioPortal via its keyless REST API for cancer genomics across TCGA, GENIE, MSK-IMPACT and hundreds of studies — somatic mutations, copy-number alterations (GISTIC), mRNA/protein expression, structural variants, and patient-level clinical/survival data. Use when asked how often a gene is mutated/amplified/deleted in a tumor type, to profile oncogenes or tumor suppressors across cancers (pan-cancer alteration frequency), to pull patient-level mutations joined to OS/clinical outcomes, or to validate a cancer target from cohort genomics. For germline variant pathogenicity use alterlab-clinvar; for mutational-signature (SBS) decomposition use alterlab-cosmic; for CRISPR/RNAi gene-dependency use alterlab-depmap; for aggregated target-disease evidence use alterlab-opentargets. Part of the AlterLab Academic Skills suite.

Expert YouTube scriptwriting skill for creators who want to write videos that hold attention, deliver value, and grow a channel. Use this skill whenever the user wants to write or improve a YouTube video script, craft a stronger hook or intro, structure a video idea, write a YouTube title or description, or plan a video outline. Triggers: "write a YouTube script", "help me script my video", "I'm making a video about", "write an intro for my video", "help me with my hook", "write a YouTube description", "how should I structure this video", "make my script more engaging", or any request related to YouTube video content. Do NOT limit to obvious script requests — if the user has a topic or idea and mentions YouTube, use this skill.

World-class voiceover expertise combining the narrative craft of documentary producers, the commercial precision of advertising agencies, and the accessibility of modern AI voice technology. Voiceover is the invisible art that makes or breaks video content. Great voiceover isn't just speaking clearly—it's performing the script in a way that creates the intended emotional response. The best voiceover work understands pacing, tone, emphasis, and the subtle art of making scripted words sound natural. It knows when to use human talent versus AI, and how to get the best from both. Use when "voiceover, voice over, VO, narration, narrator, voice recording, voice talent, voice actor, AI voice, text to speech, audio narration, voice direction, voiceover, audio, narration, voice, recording, AI-voice, talent, direction" mentioned.

When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' 'optimize for Claude/Gemini,' 'llms.txt,' 'OKF,' 'Open Knowledge Format,' 'knowledge bundle,' or 'agent-readable site.' Use this whenever someone wants their content to be cited or surfaced by AI assistants and AI search engines. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema.

Plan a field event, dinner, or conference presence that actually produces pipeline, not just badges scanned. It builds the right guest list, designs a draw worth showing up for, plans the on-site motion so conversations happen, and writes the follow-up that converts, because the pipeline is made after the event, not at it. Built for B2B field marketing and sales teams, customizable to your CRM and your event motion. Trigger on "plan a field event", "customer dinner plan", "conference presence", "how do I get pipeline from this event", "event guest list", "event follow-up plan", or any field-event or in-person pipeline request.

Apply Boyd's OODA loop to navigate fast-moving, uncertain, or competitive situations — Observe what is actually happening, Orient through mental models and context, Decide on the clearest path, Act quickly, then loop again. Load when the situation is changing faster than the current plan, when a competitive response is needed, when the user is stuck in analysis paralysis in a dynamic environment, when shipping under uncertainty, or when deep-thinking diagnoses a fast-moving / competitive frame. Triggers on "what should we do right now", "the situation is changing", "how do we respond to this", "competitive response", "we need to move fast", or "we're stuck deciding". Based on John Boyd's OODA loop — Observe, Orient, Decide, Act — adapted for product and business contexts (OODA Canvas 2026).

Analyze and optimize X (Twitter) posts for viral potential and reach using heuristics inspired by X's published open-source recommendation architecture. Use when user wants to: (1) Check if a post will go viral, (2) Score a tweet for engagement potential, (3) Optimize or rewrite a tweet for algorithmic reach, (4) Understand why a tweet underperformed, (5) Build audience in a specific niche. Triggers: "Check if this will go viral", "Make this post buzz", "Will this tweet perform well?", "Optimize my tweet", "How can I make this viral?", "rewrite this tweet", "improve my tweet engagement", "twitter algorithm", "tweet reach", "debug underperforming tweet", "バズるかチェックして", "Xでバズる投稿にして", "伸びるかチェックして", "この投稿を伸ばして", "投稿を改善して", "ツイートを最適化して"

Coordinate agents via the AMQ CLI for file-based inter-agent messaging. Use this skill whenever you need to send messages to another agent (codex, claude, or any named handle), check your inbox, drain queued messages, set up co-op mode between agents, join a swarm team, route messages across projects, or diagnose delivery issues. Also use it when you receive a message and need to know how to reply, inspect receipts, or handle priority. Covers any multi-agent coordination task where agents need to talk to each other — review requests, questions, status updates, decision threads, wake notifications, and orchestrator integration (Symphony, Kanban). For collaborative spec/design workflows specifically, prefer the /amq-spec skill which provides structured phase-by-phase guidance. Not intended for distributed systems design (RabbitMQ, Kafka), CI/CD pipelines, or single-agent tasks with no partner.

When the user wants to figure out which marketing actually drives conversions and revenue, choose or interpret an attribution model, or reconcile conflicting numbers across tools. Also use when the user mentions "attribution," "attribution model," "first-touch vs last-touch," "multi-touch," "which channel drives revenue," "what's my real CAC," "my dashboards disagree," "Google/Meta says X but GA says Y," "media mix model," "MMM," "incrementality," "geo lift," "holdout test," "how did you hear about us," "self-reported attribution," "dark social," or wants to instrument attribution themselves — "stitch my bookings to their source," "SavvyCal/Calendly attribution," "close the identify gap," "track conversions on a third-party domain," "first-party / self-hosted attribution." For event tracking setup and UTMs, see analytics. For ad-platform pixels/CAPI, see ads. For pipeline and CRM revenue reporting, see revops. For the AI-search attribution blind spot, see ai-seo.

Expert product strategy advisor for Senior PMs. Use this skill — proactively and without waiting to be asked — whenever defining a product vision, setting quarterly OKRs, building a roadmap, choosing between competing bets, entering a new product area, or when stakeholders disagree on direction. Also triggers for: "what should we prioritize", "we need a north star", "how do we choose between X and Y", "roadmap conflict", "what are our bets this quarter", "strategy alignment", "choosing what NOT to build", "three bets with trade-offs", "stakeholder misalignment on direction", "product direction for next quarter", "OKR planning". Produces a decision-focused strategy doc: North Star metric, Opportunity Tree, three bets with explicit trade-offs (including do nothing), and a recommended bet with its key assumption.

When the user wants help with public relations, earned media, press coverage, journalist outreach, or media strategy (not pull requests). Also use when the user mentions 'PR,' 'public relations,' 'press,' 'press release,' 'press coverage,' 'media outreach,' 'pitch a journalist,' 'get featured,' 'media list,' 'media kit,' 'press kit,' 'newsjacking,' 'news hijack,' 'HARO,' 'Qwoted,' 'Featured,' 'Help A Reporter,' 'reporter request,' 'tech press,' 'TechCrunch,' 'earned media,' 'thought leadership placement,' 'op-ed,' 'guest article,' 'press contacts,' or 'how do I get press.' Use this for earned media work — finding journalists, pitching stories, newsjacking, and responding to press requests. For startup/SaaS/AI directory submissions, see directory-submissions. For product launches, see launch. For social-media engagement, see social. For cold-email outreach to prospects, see cold-email.

Performs deep architectural analysis of a specified module, directory, or feature area by examining structural coupling, data flow, concurrency patterns, risk, and SOLID alignment. Use when the user wants to assess, evaluate, or review the architecture, design quality, dependency structure, coupling, cohesion, or technical debt of an existing part of the codebase. Not for investigating specific bugs, runtime errors, or failures — use investigate. Not for test planning — use automated-test-planning. Not for file-level code review — use code-review. Not for researching open-ended options, prior art, or how something works — use research. Not for designing a new interface or contract — use design-an-api. Not for writing documentation or architectural decision records.

Implementation and taxonomy skill for analytics tracking — event naming, properties, tracking plans, GA4/GTM/Amplitude setup, and debugging. Use this for the "how do we actually wire this up" layer, not the "what should we measure and why" layer (that's `product-analytics` — use this skill alongside it, after the metrics/tracking-plan decisions are made). Use this — without waiting to be asked — whenever the user mentions "set up tracking," "GA4," "Google Analytics," "Amplitude," "event tracking," "UTM parameters," "tag manager," "GTM," "tracking plan," "event taxonomy," "are my events firing," "why isn't this event showing up," "naming convention for events," or "instrument this feature." Produces a concrete tracking plan (event names, properties, triggers) plus implementation and debugging steps for the tools actually in use.

When the user wants multiple expert perspectives on a marketing question — a simulated board of advisors staffed by legendary marketers (Seth Godin, David Ogilvy, Eugene Schwartz, April Dunford, Rory Sutherland, Alex Hormozi, Byron Sharp, and more). Also use when the user mentions 'marketing council,' 'board of advisors,' 'advisory board,' 'what would Seth Godin say,' 'what would Ogilvy think,' 'channel Hormozi,' 'get multiple perspectives,' 'debate this,' 'have the council review,' 'marketing mentors,' or asks how a famous marketer would approach their problem. The council gives each advisor's take through their documented frameworks, surfaces where they disagree, and synthesizes a recommendation. For executing the winning direction, hand off to positioning, offers, copywriting, ads, or the relevant skill.

Design the architecture for a multi-command skill system — the shared state schema, the command map, the router, and the boundary each command stops at — before any skill files get written. Use when the user wants to turn one skill into a system, combine several related or overlapping skills into a single coherent one, build a skill with subcommands (like `/thing audit`, `/thing polish`), design a suite, family, or collection of skills, or asks "how should I structure this skill set". Also trigger on "skill system", "skill architecture", "multi-command skill", "system of skills", "make these skills work together", "skill with slash commands", or complaints that their skills overlap, collide, duplicate each other, or never fire. Produces an architecture spec only — it never writes SKILL.md or reference files. Hand the finished spec to skill-creator to build from.

Expert email writing skill for professionals and individuals. Use this skill whenever the user wants to write, draft, improve, or get help with ANY email — including cold outreach, follow-ups, complaints, negotiations, thank-you notes, difficult conversations, reconnection emails, or any other professional or personal email. Also trigger for email marketing requests: promotional offers, newsletters, welcome emails, re-engagement campaigns, or clickbait-style emails. Trigger for: "help me write an email", "draft an email", "how should I phrase this email", "I need to reach out to someone", "I need to follow up", "I want to send a thank you", "I have a complaint to write", "write a newsletter", "create a welcome email", "write a promotional email", "re-engage my subscribers", or any situation where someone needs to communicate via email. Do NOT limit this to obvious requests — if the user describes a situation where an email would be the right output, use this skill proactively.

Run any model on RunComfy from the command line. The `runcomfy` CLI is one binary, one auth, hundreds of model endpoints — image generation, image edit, video generation, image-to-video, lip-sync, face swap, video edit, inpainting, outpainting, extend, ControlNet, relight, upscale, LoRA training and more. Submit a request, poll for status, download the output. This skill teaches the agent how to install, authenticate, discover model schemas, invoke models, stream / poll / no-wait, script in JSON output mode, and handle errors. Triggers on "runcomfy cli", "install runcomfy", "runcomfy login", "runcomfy run", "runcomfy whoami", "runcomfy api", or any explicit ask to call a RunComfy model from a script or terminal. Sibling skills (ai-image-generation, ai-video-generation, image-edit, video-edit, face-swap, lipsync, image-to-video, image-inpainting, image-outpainting, video-extend, controlnet-pose, relight) all dispatch through this CLI.