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Found 1,150 Skills
Comprehensive code review checklist for Go projects. Evaluates code quality, idiomatic patterns, error handling, naming, package structure, and test coverage. Use when reviewing Go code, PRs, or before merging changes. Trigger examples: "review this code", "check this PR", "code review", "review Go file". Do NOT use for security-specific audits (use go-security-audit) or performance-specific analysis (use go-performance-review).
Audit Go module dependencies: detect outdated packages, check for known vulnerabilities, review go.mod hygiene, identify unused or redundant deps, and evaluate dependency quality. Use when auditing dependencies, checking for CVEs, cleaning up go.mod, upgrading modules, or evaluating third-party packages. Trigger examples: "check dependencies", "audit deps", "go.mod review", "update modules", "vulnerability scan", "govulncheck". Do NOT use for code-level security issues (use go-security-audit) or architecture review (use go-architecture-review).
Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation, Trackio monitoring, and Hub persistence. Use when users mention training object detection, image classification, SAM, SAM2, segmentation, image matting, DETR, D-FINE, RT-DETR, ViT, timm, MobileNet, ResNet, bounding box models, or fine-tuning vision models on Hugging Face Jobs.
Analyzes living systems and biological phenomena through biological lens using evolution, molecular biology, ecology, and systems biology frameworks. Provides insights on mechanisms, adaptations, interactions, and life processes. Use when: Biological systems, health issues, evolutionary questions, ecological problems, biotechnology. Evaluates: Function, structure, heredity, evolution, interactions, molecular mechanisms.
Scaffolds eval.yaml test files for agent skills in the dotnet/skills repository. Use when creating skill tests, writing evaluation scenarios, defining assertions and rubrics, or setting up test fixture files. Handles eval.yaml generation, fixture organization, and overfitting avoidance. Do not use for running or debugging existing tests nor for skills authoring.
Research and analyze tokens on supported blockchains: search tokens by keyword, get token details (price, market cap, volume, supply), run security audits (honeypot, mint risk, proxy, tax), list DEX liquidity pools, view top holders, find smart money traders, and retrieve K-line candlestick chart data. Trigger words: token, coin, search token, find token, look up token, token info, token details, token data, token price, price of, how much is, what is the price, market cap, market capitalization, volume, trading volume, supply, total supply, circulating supply, FDV, fully diluted valuation, token security, security audit, is it safe, honeypot, rug pull, mint risk, proxy contract, buy tax, sell tax, token pools, liquidity pools, DEX pools, trading pools, LP, liquidity, token holders, top holders, who holds, whale holders, holder distribution, token traders, smart money, smart traders, KOL traders, top traders, candles, candlestick, K-line, kline, price chart, price history, OHLCV, token analysis, token research, due diligence, DYOR, check token. Chinese: 代币, 搜索代币, 查代币, 代币信息, 代币详情, 代币价格, 价格多少, 市值, 交易量, 总供应量, 代币安全, 安全审计, 是否安全, 蜜罐, 貔貅, 池子, 流动性, 持有者, 大户, 鲸鱼, 交易者, 聪明钱, K线, 蜡烛图, 价格走势. CRITICAL: Always use `--json` flag for structured output. CRITICAL: When user asks about token safety, ALWAYS run `token security` — do not guess. Do NOT use this skill for: - Trending token rankings or new token discovery → use liberfi-market - Wallet holdings, activity, or PnL stats → use liberfi-portfolio - Swap quotes, trade execution, or transaction broadcast → use liberfi-swap - General market trends without a specific token → use liberfi-market Do NOT activate on vague single-word inputs like "token" or "coin" without additional context specifying a search query, chain, or address.
Evaluate the output of a journey-builder run, identify instruction gaps, and edit the project root AGENTS.md (or add pitfalls to the gist) to fix those gaps. Does NOT modify the journey-builder skill itself.
Invoke this skill when a user shares test code and questions whether it actually works as intended — not to run or fix the test, but to evaluate whether the test has real value. Triggers on: "is this test any good?", "would this catch a real bug?", "this test always passes — is that normal?", "review these tests before I commit", or "does this test verify anything meaningful?". Also triggers when someone suspects a test is useless, wants a pre-commit quality gate, or is unsure if an auto-generated test is worth keeping. The core question this skill answers: "Would this test fail if the feature broke?" If not, the test gets rejected. Do NOT use for generating new tests, fixing failing tests, or exploring application features.
This skill should be used when the user asks to "audit a website for AI visibility", "scan a domain", "check AI readiness", "evaluate content quality", "run a Morphiq Scan", "check if a site is optimized for LLMs", or mentions scanning a website for LLM citation readiness. Performs a full AI visibility audit across 5 categories (agentic readiness, content quality, chunking & retrieval, query fanout, policy files) and scores the domain on a 100-point rubric.
Provides comprehensive memory file management capabilities including auditing, quality assessment, and targeted improvements for files such as CLAUDE.md. Use when user asks to check, audit, update, improve, fix, maintain, or validate project memory files. Also triggers for "project memory optimization", "CLAUDE.md quality check", "documentation review", or when a project memory file needs to be created from scratch. This skill scans memory files, evaluates quality against standardized criteria, outputs detailed quality reports with scores and recommendations, then makes targeted updates with user approval.
Analyze competitor pricing strategies across e-commerce platforms. Map price positions, identify pricing gaps, evaluate price elasticity signals, and develop data-driven pricing strategies.
Product research for dropshipping businesses. Identify profitable products with reliable suppliers, healthy margins, and manageable competition. Evaluates shipping times, return risk, and marketing viability.