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Found 753 Skills
Help the user shape technical blog posts, website articles, devlogs, essays, or long-form drafts without writing the full post for them. Use this whenever the user shares rough notes, a brain dump, unordered ideas, bullet points, or half-written sections, or asks for help turning notes into an outline, finding the angle, sharpening the hook or thesis, improving structure, clarifying the argument, tightening flow, stress-testing the payoff, or making a technical piece more engaging while preserving their voice. Use it even if the user does not explicitly ask for a writing guide, as long as they need help organizing and developing a post rather than having it ghostwritten. Guide with organization, critique, focused questions, and tiny example lines only; do not write the final article.
Apply when deciding, designing, or implementing FastStore theme customizations in src/themes/ or working with design tokens and SCSS variables. Covers global tokens, local component tokens, Sass variables, CSS custom properties, and Brandless architecture. Use for any visual customization of FastStore storefronts that does not require component overrides.
Analyze an unfamiliar repository and explain what it does, how it runs, what architectural choices define it, where the important code lives, and what deserves deeper inspection next. Use this whenever a user has just cloned a repo, wants onboarding help, asks for a repo walkthrough, or needs a reliable first-pass architecture analysis.
Recovery strategy when the Write tool fails to create a new file. Use this skill whenever a Write or Edit tool call fails with an error related to creating a new file — such as missing parent directories, permission issues, or "file not found" errors on files that don't exist yet. This skill does NOT apply to editing existing files that fail for other reasons. Trigger when you see Write/Edit errors on new file creation, when file creation fails unexpectedly, or when you get path-related errors trying to create files in nested directories.
Write and maintain an implementation diary capturing what changed, why, what worked, what failed (with exact errors and commands), what was tricky, and how to review and validate. Activates proactively during non-trivial implementation work (new features, bug fixes, refactors, research spikes). Does not activate for trivial tasks like one-line fixes, config tweaks, or quick questions.
Alibaba Cloud Security Center (SAS) Overview Data Query Skill. Retrieves security score, asset status, risk governance, asset risk trends, and billing info. Supports flexible scope: query a single data item, a specific module, or the full overview based on user intent. Triggers: "SAS overview", "security center overview", "SAS 总览", "云安全中心总览", "security score", "安全评分", "安全分", "vulnerability fix", "baseline risk", "handled alerts", "host assets", "uninstalled clients", "risk governance", "WAF blocks", "asset risk trend", "SAS billing", "订阅状态", "账单" Out of scope: This Skill only covers SAS overview data queries. It does not perform remediation, modify configurations, or manage non-SAS services.
Use when a task fails, an approach does not work, when encountering errors during implementation, or when tempted to say "I cannot do this" - ensures retry with at least 3 genuinely different approaches before escalating
Fetch structured stock sentiment across Reddit, X.com, news, and Polymarket using the Adanos Finance API. Use this skill whenever the user asks how much people are talking about a stock, how hot a ticker is on social platforms, how many Polymarket bets exist for a company, whether sources are aligned, or to compare stock sentiment across multiple tickers. Triggers include: "social sentiment on TSLA", "how hot is NVDA on X.com", "how many Reddit mentions does AAPL have", "compare sentiment on AMD vs NVDA", "how many Polymarket bets on Microsoft", "is Reddit aligned with X on META", "stock buzz", "bullish percentage", and any mention of cross-source stock sentiment research. This skill is READ-ONLY and does not place trades or modify anything.
A comprehensive Git command assistant and workflow guide. Trigger whenever the user asks how to perform a specific Git operation, wants to know what a Git command does, needs help fixing a Git mistake, or wants guidance on Git best practices (like branching, rebasing, or squashing).
Set up and improve harness engineering (AGENTS.md, docs/, lint rules, eval systems, project-level prompt engineering) for AI-agent-friendly codebases. Triggers on: new/empty project setup for AI agents, AGENTS.md or CLAUDE.md creation, harness engineering questions, making agents work better on a codebase. ALSO triggers when users are frustrated or complaining about agent quality — e.g. 'the agent keeps ignoring conventions', 'it never follows instructions', 'why does it keep doing X', 'the agent is broken' — because poor agent output almost always signals harness gaps, not model problems. Covers: context engineering, architectural constraints, multi-agent coordination, evaluation, long-running agent harness, and diagnosis of agent quality issues.
Discovers business domains in a Swift codebase by tracing what users can DO — not by reading folder names or architecture docs. Maps each domain's vertical slice (Types → Config → Repo → Service → Runtime → UI), identifies providers (external SDK bridges), and separates cross-cutting concerns. Produces a domain map that drives all downstream decisions: folder structure, SPM targets, enforcement specs, migration plans. Use this skill whenever the user wants to understand their codebase domains, find what's cross-cutting vs domain-specific, restructure a Swift project, figure out where code belongs, or map a product's capabilities to architectural boundaries. Triggers on "what are my domains", "where does this belong", "map this codebase", "what's cross-cutting", "organize this project", "is this a domain or infra", "restructure this", "architecture review", or any request to understand the business domain structure of a Swift codebase.
Fetch dependency source code to give AI agents deeper implementation context. Use when the agent needs to understand how a library works internally, read source code for a package, fetch implementation details for a dependency, or explore how an npm/PyPI/crates.io package is built. Triggers include "fetch source for", "read the source of", "how does X work internally", "get the implementation of", "opensrc path", or any task requiring access to dependency source code beyond types and docs.