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marketing-loops
当用户想要设置一个定期、自动运行的营销工作流——即AI代理按节奏(每周、每天、触发时)运行的重复循环,而非一次性任务时使用。也适用于用户提及“营销循环”、“定期营销工作流”、“自动化营销”、“自动营销”、“每周营销回顾”、“广告疲劳检查”、“内容刷新循环”、“流失监控”、“排名下降提醒”、“始终在线营销”、“营销自动化工作流”或“每周运行此任务”时。使用此技能来选择、调整和安排一个持续的营销循环,以协调其他营销技能。对于一次性营销创意,请参见 marketing-ideas。对于专门的实验循环,请参见 ab-testing。
coreyhaines31
salesforce-flow-design
Salesforce Flow architecture decisions, flow type selection, bulk safety validation, and fault handling standards. Use this skill when designing or reviewing Record-Triggered, Screen, Autolaunched, Scheduled, or Platform Event flows to ensure correct type selection, no DML/Get Records in loops, proper fault connectors on all data-changing elements, and appropriate automation density checks before deployment.
github
hermes-tweet
Install and operate Hermes Tweet, a Hermes Agent plugin for X/Twitter research, timeline reading, tweet analysis, and approval-gated private or state-changing operations. Use this skill when installing Hermes Tweet, researching X/Twitter accounts, monitoring launch signals, investigating mentions, auditing giveaways, or preparing gated X operations. Use proactively when a Hermes Agent workflow needs current X/Twitter context. Requires XQUIK_API_KEY for read and action tools.
wshobson
autopilot
Full autonomous execution from idea to working code
yeachan-heo
deepinit
Deep codebase initialization with hierarchical AGENTS.md documentation
yeachan-heo
react-audit-grep-patterns
Provides the complete, verified grep scan command library for auditing React codebases before a React 18.3.1 or React 19 upgrade. Use this skill whenever running a migration audit - for both the react18-auditor and react19-auditor agents. Contains every grep pattern needed to find deprecated APIs, removed APIs, unsafe lifecycle methods, batching vulnerabilities, test file issues, dependency conflicts, and React 19 specific removals. Always use this skill when writing audit scan commands - do not rely on memory for grep syntax, especially for the multi-line async setState patterns which require context flags.
github
hypothesis-generation
Formulate evidence-bounded scientific questions, candidate hypotheses, rival explanations, causal or associational claims, discriminating predictions, measurements, and preregistration-ready analysis plans. Use when turning observations or preliminary findings into transparent, testable research plans without treating hypotheses as facts.
k-dense-ai
scholar-evaluation
Provide qualitative-first, evidence-traceable developmental review of scholarly works and audit low-stakes research-assessment rubrics with optional local quality controls. Never use for ranking people or consequential decisions.
k-dense-ai
database-lookup
Query documented public database APIs with explicit endpoints, filters, pagination, and provenance. Use when a scientific, regulatory, financial, or other database-backed fact must be retrieved reproducibly from a named source rather than inferred from general knowledge.
k-dense-ai
bgpt-paper-search
Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server. Returns 25+ fields per paper including methods, results, sample sizes, quality scores, and conclusions. Use for literature reviews, evidence synthesis, and finding experimental details not available in abstracts alone.
k-dense-ai
pptx-posters
Create and audit editable scientific posters in macro-free PowerPoint (.pptx) from author-approved local content and assets. Use when the requested deliverable is a PowerPoint research/conference poster and exact physical, printer, accessibility, provenance, and package-security checks are required.
k-dense-ai
polars
High-performance DataFrame library for Python ETL, analytics, and pandas migration. Use for expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU execution.
k-dense-ai
latex-posters
Create professional research posters in LaTeX using beamerposter, tikzposter, or baposter. Support for conference presentations, academic posters, and scientific communication. Includes layout design, color schemes, multi-column formats, figure integration, and poster-specific best practices for visual communication.
k-dense-ai
xlsx
Create, edit, analyze, or convert Excel spreadsheets (.xlsx, .xlsm, .xltx) where the workbook file is the primary deliverable. Use for formulas, formatting, financial models, multi-sheet workbooks, and tabular cleanup exported to Excel. Also applies to .csv/.tsv when the user wants spreadsheet output. Do NOT use for Word documents, HTML reports, standalone Python scripts, database pipelines, or Google Sheets API work.
k-dense-ai
research-grants
Write competitive research proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC. Agency-specific formatting, review criteria, budget preparation, broader impacts, significance statements, innovation narratives, and compliance with submission requirements.
k-dense-ai
salesforce-apex-quality
Apex code quality guardrails for Salesforce development. Enforces bulk-safety rules (no SOQL/DML in loops), sharing model requirements, CRUD/FLS security, SOQL injection prevention, PNB test coverage (Positive / Negative / Bulk), and modern Apex idioms. Use this skill when reviewing or generating Apex classes, trigger handlers, batch jobs, or test classes to catch governor limit risks, security gaps, and quality issues before deployment.
github
hud
Configure HUD display options (layout, presets, display elements)
yeachan-heo
ralplan
Consensus planning entrypoint that auto-gates vague ralph/autopilot/team requests before execution
yeachan-heo
python-pypi-package-builder
End-to-end skill for building, testing, linting, versioning, and publishing a production-grade Python library to PyPI. Covers all four build backends (setuptools+setuptools_scm, hatchling, flit, poetry), PEP 440 versioning, semantic versioning, dynamic git-tag versioning, OOP/SOLID design, type hints (PEP 484/526/544/561), Trusted Publishing (OIDC), and the full PyPA packaging flow. Use for: creating Python packages, pip-installable SDKs, CLI tools, framework plugins, pyproject.toml setup, py.typed, setuptools_scm, semver, mypy, pre-commit, GitHub Actions CI/CD, or PyPI publishing.
github
react19-source-patterns
Reference for React 19 source-file migration patterns, including API changes, ref handling, and context updates.
github
ai-slop-cleaner
Clean AI-generated code slop with a regression-safe, deletion-first workflow and optional reviewer-only mode
yeachan-heo
mcp-security-audit
Audit MCP (Model Context Protocol) server configurations for security issues. Use this skill when: - Reviewing .mcp.json files for security risks - Checking MCP server args for hardcoded secrets or shell injection patterns - Validating that MCP servers use pinned versions (not @latest) - Detecting unpinned dependencies in MCP server configurations - Auditing which MCP servers a project registers and whether they're on an approved list - Checking for environment variable usage vs. hardcoded credentials in MCP configs - Any request like "is my MCP config secure?", "audit my MCP servers", or "check .mcp.json" keywords: [mcp, security, audit, secrets, shell-injection, supply-chain, governance]
github
phoenix-cli
Debug LLM applications using the Phoenix CLI. Fetch traces, analyze errors, structure trace review with open coding and axial coding, inspect datasets, review experiments, query annotation configs, and use the GraphQL API. Use whenever the user is analyzing traces or spans, investigating LLM/agent failures, deciding what to do after instrumenting an app, building failure taxonomies, choosing what evals to write, or asking "what's going wrong", "what kinds of mistakes", or "where do I focus" — even without naming a technique.
github
onboard-context-matic
Interactive onboarding tour for the context-matic MCP server. Walks the user through what the server does, shows all available APIs, lets them pick one to explore, explains it in their project language, demonstrates model_search and endpoint_search live, and ends with a menu of things the user can ask the agent to do. USE FOR: first-time setup; "what can this MCP do?"; "show me the available APIs"; "onboard me"; "how do I use the context-matic server"; "give me a tour". DO NOT USE FOR: actually integrating an API end-to-end (use integrate-context-matic instead).
github