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Found 2,043 Skills
Agent simulation and GEO simulation prompt generation for AI visibility auditing. Use when the user wants to create simulation tasks via the TPC CLI, generate unbranded GEO prompts to test whether AI recommends a product, or run agent simulations.
Account statements (daily / monthly) via Longbridge Securities — list available statements and export sections (equity holdings, cash transactions, fees, etc.) as CSV or markdown for accounting, tax filing, or audit. Also covers bank cards linked to the account, withdrawal history, and deposit history. Requires longbridge login with Trade scope. Read-only — no order placement here. Triggers: "对账单", "月结单", "日结单", "账单导出", "税务报表", "报税资料", "导出持仓", "导出交易记录", "银行卡", "出金记录", "入金记录", "充值记录", "對賬單", "月結單", "日結單", "賬單導出", "稅務報表", "報稅資料", "銀行卡", "出金記錄", "入金記錄", "account statement", "monthly statement", "daily statement", "export statement", "tax report", "bank cards", "withdrawal history", "deposit history", "1099", "year-end statement".
Audit a directory of multilingual blog content for completeness, consistency, hreflang correctness, meta-tag parity, and freshness. Builds a translation coverage matrix, flags stale translations, validates hreflang and schema, and emits a prioritized report with runnable fix commands. Use when user says "locale audit", "blog locale-audit", "check translations", "multilingual audit", "translation check", "hreflang check", "Uebersetzungen pruefen".
SEO & content marketing automation skill suite with keyword research, technical audits, SERP analysis, and content optimization workflows
Adversarial robustness engineering for ML/AI—evasion, poisoning, extraction, membership-inference threat models; robust training, sanitization, detectors; ASR/certified evals; lab model attacks; data-pipeline integrity; production I/O guardrails (classical ML and LLM/multimodal). Use for adversarial examples, robustness suites, poison audits, deploy guardrails—not LLM app red team (ai-redteam), governance (ai-risk-governance), safety classifier R&D (ml-research-engineer-safeguards), safeguard serving (ml-infrastructure-engineer-safeguards), privacy research (privacy-research-engineer-safeguards), AppSec pentest (penetration-tester).
Use when ANY command fails with 'command not found', when installing CLI tools (ripgrep, fd, jq, yq, bat, etc.), auditing project environments, or batch-updating tools. Triggers on: command not found, install tool, missing binary, environment audit, update tools, which, apt install, brew install.
Meta-skill that forges, audits, and refines other skills. Three modes – forge a new skill from a brief, audit recent chat transcripts for new-skill candidates and pain points, or refine an existing skill with additive-only changes. Triggers on "skill-forge a thing that does X", "forge a skill", "skill-forge audit", "skill audit", "refine my skills", "skill-forge refine <name>", or "/skill-forge". Auto-opens a PR against mphinance/alpha-skills (never auto-merges).
Control a Chrome browser session through the chrome-devtools-axi CLI - navigate, snapshot, click, fill forms, run JavaScript, inspect console and network, take screenshots, audit performance. Use whenever a task needs a real browser: opening or testing a web page, clicking through a flow, extracting page content, or debugging a website.
Luban - Skill Polishing Workshop. Transform a "usable Skill" into a public Skill asset that is "understandable, installable, shareable, verifiable, and continuously evolvable". The methodology consists of five craftsman-like steps: 1. Material Inspection: First challenge whether the premise of this Skill is valid; directly state if the "material" is not worth polishing. 2. Peer Research: Search for similar Skills online to clarify its position in the ecosystem. 3. Dimension Measurement: Evaluate using three metrics - structure, actual testing, and live verification (live verification means reconciling with real running outputs; a green CI can be deceptive). 4. Iterative Refinement: Freeze the original version as a baseline; only retain changes that pass the verification gate, otherwise revert. Try to institutionalize verification methods as tools and rules in the repository. 5. Post-Release Iteration: Release is not the end; maintain a benchmark observation list, and start the next iteration based on real feedback. This tool is used when users want to upgrade, optimize, polish, productize, or release their self-developed Skills. The final deliverables include a structured Skill Polishing Report, directly replaceable rewritten segments, and a shareable "Graduation Certificate" result card that can be screenshot. Trigger phrases include but are not limited to: "Let Luban take a look at this skill", "Polish at Luban's Workshop", "Polish my skill", "Upgrade my skill", "Optimize this skill", "Skill check-up", "Skill audit", "Productize my skill", "How to release this skill", "Benchmark against similar skills", "Why no one installs my skill", "Help me publish my skill to GitHub/ClawHub", "Improve SKILL.md". Even if users only provide a Skill directory, GitHub repository link, or a segment of SKILL.md saying "Help me figure out how to modify it", it should be triggered as long as the context is about making the Skill more usable and shareable. Do NOT use this for creating a new Skill from scratch (use skill-creator), regular code review (use code-review), or rewriting ordinary prompts unrelated to Skill assets.
Detect and fix silent Amazon category re-noding. When Amazon quietly moves listings to incorrect browse-tree nodes, sales drop sharply because the listing now ranks against the wrong queries. This skill audits the nodes, identifies the wrong placements, and writes the browse-node correction case for Seller Central. Use when a user notices a sudden sales drop with flat ad spend, a listing in the wrong browse category, or wonders why their product is not showing up for the right keywords. Trigger phrases: "category", "browse node", "wrong category", "re-noded", "sales dropped no reason", "browse tree". Works with zero tools.
Migrate Exa, Tavily, Perplexity, or Firecrawl web-data integrations completely to the appropriate Parallel products while preserving application behavior. Use when replacing these providers' SDKs or REST calls, dependencies, environment variables, request parameters, response parsing, model tools, search-plus-scrape paths, full-content or answer-synthesis paths, tests, and documentation; separating unsupported research-index, crawl, browser, file-parse, monitor, or other non-search capabilities; auditing for leftover provider usage; or finishing and verifying an in-progress provider migration.
Scans Algorand smart contracts for 11 common vulnerabilities including rekeying attacks, unchecked transaction fees, missing field validations, and access control issues. Use when auditing Algorand projects (TEAL/PyTeal).