Sno Station
Sno Station은 AI 에이전트를 하나의 팀으로 묶는 오픈소스 워크스테이션으로, 로컬 머신에서 에이전트 협업을 가능하게 함
AI 가시성·지리·AEO·SEO 콘텐츠·디지털 PR을 위한 공식 Machine Relations 스킬
The official Machine Relations skill for AI visibility, GEO, AEO, SEO content and digital PR: evidence, a usable intervention brief and an outcome test.
플러그인JavaScriptGitHub @Bramwell-Inc온라인운영자 미확인
써 보셨어요? 한 번만 눌러 주세요. 로그인은 필요 없어요.
개인 계정의 공개 저장소 소유자는 GitHub로 로그인해 운영자를 확인하고 소개를 직접 관리할 수 있습니다. 관리자 승인은 필요하지 않습니다.
로그인한 뒤 확인 파일을 만들어 이 저장소의 기본 브랜치에 30분 안에 커밋해 주세요. 다른 브랜치나 포크의 파일은 인정하지 않습니다. 파일을 올린 뒤 아래에서 확인하면 관리자 승인 없이 관리할 수 있습니다. 자격을 유지하려면 파일을 남겨 두세요.
로그인이 필요하면 로그인 화면으로 이동합니다. 로그인 후 이곳으로 돌아와 원하는 확인 버튼을 다시 눌러 주세요.
프로젝트 폴더에서 /nomorevibe verify를 실행하면 소유권을 확인하고 소개를 직접 관리할 수 있습니다.
1분 만에 확인하기Official Machine Relations skill and MRI research tools for AI visibility, GEO/AEO, SEO content discovery and digital PR.
저장소 README에서 가져옴
README 전체를 불러오는 중입니다.
README 전문 보기 ↗The official Machine Relations skill and plugin helps practitioners choose and draft an evidence-backed authority intervention for a brand or client. It supports AI visibility, GEO/AEO, SEO content discovery and digital PR work, with separate execution checks and intended-outcome tests. No AuthorityTech purchase is required.
The package includes the broader machine-relations skill alongside the existing machine-relations-index research skill. The Machine Relations Index (MRI) by Jaxon Parrott remains neutral public measurement of which source domains AI answer engines cite in sampled buyer answers, by category and question shape. Broader work can also use public or client-supplied evidence without MRI coverage.
The plugin retains the package identifier machine-relations-index and remote MCP server at https://machinerelations.ai/mcp (read-only, no account). Its four research tools are unchanged:
| Tool | What it answers |
|---|---|
mri_list_categories | Which categories, question shapes and source roles the Index covers |
mri_get_category | One category's question shapes and whether each has published rates |
mri_get_cited_sources | The ranked source domains AI engines cite for a category and question shape |
mri_get_domain | How often a site is cited, by which engines, and where it ranks |
Codex
codex plugin marketplace add Bramwell-Inc/machinerelations-plugins
Then install the Machine Relations package (identifier machine-relations-index) from that marketplace. Published directory versions may still display Machine Relations Index; verify that your installed version includes machine-relations before expecting the broader workflow.
Claude Code
/plugin marketplace add Bramwell-Inc/machinerelations-plugins
/plugin install machine-relations-index@machinerelations
Any MCP client: add a remote (streamable HTTP) server with URL https://machinerelations.ai/mcp. It is also listed in the official MCP Registry as ai.machinerelations/mri.
No MCP: the same reads are a JSON API at https://machinerelations.ai/api/mri/v2 (OpenAPI).
An MCP connection alone supplies research tools; it does not install the skill. The broader skill is at plugins/machine-relations-index/skills/machine-relations/SKILL.md for compatible skill hosts. New instructions do not require changing Editor's private method, the App journey or the Index's measurement.
Every response carries its release ID, the artifact hash and a citation string. MRI data is licensed CC BY 4.0. Dataset citation: Machine Relations Index (MRI) by Jaxon Parrott, Machine Relations Research — machinerelations.ai. https://machinerelations.ai/index. https://doi.org/10.5281/zenodo.23652423. Methodology: https://machinerelations.ai/machine-relations-index.
The plugin package in this repository is MIT licensed.
Start with the worked example and agent entry point. The example preserves one historical release; it is not a live leaderboard.
Every successful current data read includes source.guidance, the live interpretation rules. The skill directs agents there and to any field-specific method and limitations. Daily data and interpretation updates therefore do not require rebuilding this plugin. Missing or null question context is unavailable, never zero; the service describes what the current release actually contains.
Every version is released once, from a reviewed pull request, and the release is the single source for everything else:
SKILL.md (metadata.version), CHANGELOG.md and CITATION.cff. The Validate and package check enforces that, the exact AuthorityTech descriptor, and that no internal identifiers or secrets reach the README, changelog, citation or packaged plugin files; it also proves fresh installs in Codex and Claude Code. Semver: a minor version adds or graduates a method, a patch corrects wording or metadata, a major version changes a tool or endpoint.library.json with the reserved DOIs and refuses to continue if any other file differs from the tested build), which gives the version its own DOI, then publishes the GitHub release with library.json (every skill, version, DOI and sha256), the plugin ZIP, one archive per skill and SHA256SUMS./.well-known/agent-skills/index.json, rebuild from https://github.com/Bramwell-Inc/machinerelations-plugins/releases/latest/download/library.json. Nothing is copied by hand.Cite the library with its concept DOI, 10.5281/zenodo.23749768 (all versions); cite a version DOI only for work that used that exact version. Both are in library.json and on each release. CITATION.cff gives the author record. The library's Wikidata item is Q141909117.
A skill can carry metadata.title and metadata.summary (a human name and a one-sentence practitioner summary; not the description trigger text). Pages use them when present.
Directory listings (Claude, ChatGPT) update through their own review and can lag the latest release. The remote MCP service owns the Index's data and interpretation; daily data never requires a plugin release. The review/ captures and video are dated evidence, not current API documentation.