Total 51,486 skills
Showing 12 of 51486 skills
Guided first-run demo for the Cargo CLI — from a fresh workspace to a real deliverable (25 leads matching the user's buyer persona, with a cost receipt) in under two minutes, ending by saving the demo as a recurring play. Use when the user is new to Cargo, asks for a demo/tour/quickstart, or has an empty workspace and wants to see what the CLI can do. For real GTM work beyond the demo, route to cargo-gtm.
Complete the full loop of "Data → Fine-tuning Training → Export → Deployment → Inference" using Bailian CLI (`bl`), or deploy base models directly without training. Supports fine-tuning of text models (SFT/DPO/CPT), audio TTS models (CosyVoice), and image generation models (Wan2.7). Covers dataset validation/upload, creating fine-tuning tasks, waiting for training completion, exporting the best checkpoint, creating inference deployments, waiting for readiness, and providing inference examples. This skill should be activated when users mention actions like "training models", "fine-tuning", "fine-tune", "finetune", "deploying models", "model launch", "running/calling fine-tuned models", "training an inference model", "continuing pre-training", "LoRA/SFT/DPO training", "speech synthesis models", "TTS fine-tuning", "CosyVoice", "voice cloning", "image generation fine-tuning", "text-to-image", "image-to-image", "Wan2.7", "image model training" on Bailian / DashScope / Alibaba Cloud Model Studio — even if users don't explicitly mention "using bl", as long as the intention is training or deployment on the Bailian platform, use this skill and do not assemble commands on your own.
Identify the core constraints that truly define a domain, profession, role, product, or debate. Classify these constraints into World/Rules/Interpretation (Hard/Soft/Self-imposed) categories, then analyze how this set of constraints defines identity, completes the problem statement, frames the solution space, and explains actual behaviors. It is particularly useful for distinguishing solution divergences caused by different constraints despite the same goal, and identifying old interpretations that are mistakenly treated as hard facts. USE WHEN the user says 'constraint', 'find constraints', 'what are the constraints of this domain', 'essential constraints', 'what defines its boundaries', 'is this a hard constraint or self-imposed constraint', 'where are the boundaries', 'why does this behavior happen', 'constraint', '/ljg-constraint', or provides any domain/profession/role/product/debate and requests mapping of its defining constraints and solution space. NOT FOR deep-dive generators (use ljg-rank, which focuses on generative power rather than boundaries), vertical deep dives into a single viewpoint (use ljg-think), book decomposition (use ljg-book), or concept dissection (use ljg-learn).
Rebuild this project's MOM vault from scratch over the full captured history. Use after switching synthesis engines, recovering from a corrupted vault, or when the user explicitly asks to rebuild or regenerate memory from the beginning.
Web typography from choosing fonts to spacing, wrapping and accessibility. Use when picking or pairing typefaces, configuring variable fonts or OpenType features, setting up a type scale, styling text in components, truncating text, styling underlines, selection, placeholders or carets, or reviewing frontend code for typography. Triggers on typography, fonts, font formats, woff2, variable fonts, font-weight, opentype, font-feature-settings, letter-spacing, line-height, type scale, tabular numbers, text-wrap, truncation, line clamp, underlines, text-decoration, text selection, iOS input zoom, font smoothing, text contrast, measure, line length, text-box, smart punctuation, drop cap.
Use when configuring tsconfig, resolving TypeScript compiler errors, debugging slow type-checking or builds, fixing module resolution and ESM/CJS issues, auditing or hardening type strictness in an existing codebase, migrating JavaScript to TypeScript, migrating compiler major versions such as TypeScript 7, or setting up type-checking in monorepos. Not for general feature work that merely happens in a TypeScript codebase.
Build an iOS / Apple app on remote Xcode with `lim xcode build` instead of local xcodebuild, from any environment (Linux, Windows, macOS, VM, container). Use for non-Bazel projects (an `.xcodeproj` / `.xcworkspace`, an XcodeGen `project.yml` with a gitignored project, React Native / Expo native build) when the user wants to build, compile, reload, produce a preview build, or ship a signed device IPA. To run, tap, screenshot, or otherwise interact with the result on a simulator, use limrun-ios-simulator. For Bazel workspaces, use limrun-xcode-bazel.
Forecast cash flow under Amazon's DD+7 (Delivery-Date-Based Reserve) payout policy. Models when funds clear, sizes the working-capital buffer the seller needs, and stress-tests scenarios for slow shipping or refund spikes. Use when a user asks about DD+7, Delivery-Date-Based Reserve, payout delays, working capital, cash flow under the new reserve policy, or how much cash they need to keep on hand. Trigger phrases: "DD+7", "payout reserve", "delivery date reserve", "working capital", "cash flow", "Amazon holds my money". Works with zero tools. the user provides sales velocity, fulfillment mix, and seasonality.
Compare Amazon inbound shipment placement options (minimal-split vs Amazon- optimized split, partial-split, optional unified inventory) given SKU dimensions, units, and destination forecast. Returns the lowest landed cost per unit. Use when a user asks about STA (Send to Amazon), inbound placement fees, shipment splits, fulfillment center routing, or inbound shipping optimization. Trigger phrases: "STA", "inbound placement", "shipment split", "placement fee", "fulfillment center routing". Works with zero tools.
Audit Amazon Payments report for fee errors. Finds incorrect FBA fulfillment fees (wrong size tier), missing referral fee credits on refunds, duplicate charges, and FBA storage discrepancies, and produces an FBA fee-discrepancy case packet per finding. Use when a user asks about Amazon fee errors, overcharged fees, wrong size tier, missing referral refunds, fee audit, or Payments report analysis. Trigger phrases: "fee audit", "overcharged", "wrong fee", "size tier error", "referral fee refund", "payments report", "FBA fee dispute". Works with zero tools. the user pastes Payments report rows.
Optimize a full Amazon listing for both ranking and conversion, and diagnose why a listing is not ranking against the A9 + COSMO pillars. Rewrites the title, bullets, and description, places keywords correctly, sharpens the benefit argument, and checks policy and mobile compliance. Use when a user asks to optimize a listing, improve a title, rewrite bullets, fix a listing that does not convert, improve listing copy, do a listing makeover, rank higher in search, audit search visibility, or asks about the A9 or COSMO algorithm. Trigger phrases: "optimize my listing", "listing optimization", "rewrite my bullets", "improve my title", "listing not converting", "listing makeover", "amazon SEO", "rank higher", "A9", "COSMO", "search ranking", "search visibility", "why doesn't my listing rank". Works with zero tools.
Estimate Amazon monthly sales and revenue from a Best Seller Rank, and size a niche or competitor from observable signals. Explains the BSR-to-sales relationship, adjusts by category and price, and returns a sales range with a confidence note. Use when a user asks how many units a product sells, to estimate sales from BSR, size a market or niche, gauge a competitor's volume, or judge demand. Trigger phrases: "sales estimate", "how many units", "estimate from BSR", "best seller rank", "market size", "competitor sales", "monthly sales". Works with zero tools. the user provides BSR, category, and price.