Aigentify

io.github.pooriaarab由 GitHub 帳號 pooriaarab 發布v0.1.2更新於 Oct 24, 2026

Audit and generate agent-native product surfaces

發布方自己的服務:AI Benchmark Index

概覽

AI 產生的概覽

稽核產品目錄或線上網址對代理的友善程度,並產生 AGENTS.md、server.json 等面向代理的產物。

可以做什麼
Aigentify 提供兩個 MCP 工具:audit 接收目錄或網址,評估 agents-md、server-json、mcp、llms-txt、sitemap 等訊號,對網址還會檢查 openapi、soft-404、markdown-negotiation、rate-limit 標頭等;gen 產生 agents-md、server-json、offer、agents-route 四類產物。部分網址檢查會查詢第三方登錄檔以進行外部探索。相同功能也以 JavaScript/TypeScript 函式庫與命令列形式提供。
適用情境
當你希望助理評估某個產品或網站是否方便代理探索與使用,或起草讓它符合標準的檔案時使用。適合為代理準備文件、清單或探索中介資料的開發者。
執行需求
以 stdio 方式在本機執行,通常用 npx aigentify-mcp 或 aigentify mcp 指令啟動。需要 Node.js;處理網址目標與外部探索檢查時需要網路存取。未宣告帳號、API 金鑰或環境變數。
安裝前請注意
audit 會讀取你指定的本機目錄或抓取網址,網址檢查會向第三方登錄檔送出請求。init 與 gen 指令可能寫入 AGENTS.md、server.json 等檔案;已存在的檔案不會被更動。發布前請先檢查產生的產物。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Aigentify,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

aigentify

[npm version] [downloads/month] [license]

Package and API types · Quickstart · Configuration

aigentify is an open-source agent-readiness auditing tool for developers who maintain product directories and public websites. It returns a score, individual checks, and actionable gaps. Its TypeScript library, command-line interface (CLI), and Model Context Protocol (MCP) server also generate public artifact text.

Install

sh
npm install aigentify

Requires Node.js 20 or later. The package has five direct runtime dependencies and includes TypeScript declarations. Price: USD 0.

Run your first audit

Run this command from an existing product directory:

sh
npx aigentify audit .

No environment variables, credentials, or .env loader are required for a directory audit. The report starts with .: <score>/100, lists check statuses, and ends with Gaps:. A low score is a completed audit, not a command failure.

Generate a public guide with your product facts:

sh
npx aigentify gen agents-md --name Example --description 'A product API.' --repository https://example.com --price 0 --price-currency USD --out agents.md

Success creates agents.md. Review its placeholders and product-specific instructions before publishing it.

js
import { auditTarget, generate } from 'aigentify';
const report = await auditTarget('.');console.log(report.score, report.gaps);console.log(generate('offer', {  name: 'Example',  description: 'A product API.',  repository: 'https://example.com',  offer: { price: 0, priceCurrency: 'USD' },}));

Save this as audit.mjs and run node audit.mjs to print the score and structured offer.

How it works

text
Directory files or URL responses              |       Snapshot and checks              |       Score + ordered gaps              |  Fix product facts -> generate text -> publish -> audit again

URL audits fetch discovery endpoints and query external registries. Directory audits inspect files without running the application.

Why it exists

Developers need to check agent discovery files alongside ordinary website checks. Lighthouse audits web quality; axe-core checks accessibility. aigentify focuses on agent-facing manifests, public instructions, offers, and discovery evidence.

Compare

Scope checked on 2026-10-14. These tools address adjacent auditing needs.

ScopeaigentifyLighthouseaxe-core
Primary targetAgent readinessWeb page qualityAccessibility
Input hereDirectory or URLWeb pageHTML-based interface
Generated output hereAgent artifact textAudit reportAccessibility results

Coverage

The implementation defines 27 audit checks, six generators, and three external registry probes. These are source-checked capabilities, not evidence that every target passes them. No credential-based platform verification was performed for this rewrite.

Surface or integrationStatusScope
AGENTS.md, MCP discovery, server.jsonImplementedPresence, fields, and public-safety heuristics
Schema.org offersImplementedJSON-LD detection and urgency-language checks
llms.txt and sitemap.xmlImplementedAvailability
OpenAPI, agent manifests, /agentsImplementedURL discovery checks
Personal Agent Protocol (Poppy)ImplementedDraft 0.1 validation; discovery-only generator
HTTP discovery and crawler responsesImplementedMarkdown, links, status, body, schema, rate-limit headers
Authentication guide, API catalog, Agent2Agent cardImplementedDocument shape or availability
AI plugin manifestImplementedName, API, and authentication fields
WikidataImplementedOfficial-website lookup
npmImplementedPackage search and name/homepage matching
Official MCP RegistryImplementedServer search and name/host matching
Next.jsTemplateagents-route --framework next prints route instructions

External checks return warnings when evidence is missing or inconclusive. URL-only checks return na for local directories.

Common use cases

  1. Package maintainers audit a Node.js directory before publishing agent-facing files to npm.
  2. Next.js developers generate /agents.md route instructions, then audit the deployed URL.
  3. MCP server authors generate server-json and review its package or remote configuration.
  4. API teams inspect OpenAPI discovery, authentication guides, and Agent2Agent cards on a public URL.
  5. Product developers check Wikidata, npm, and Official MCP Registry discovery evidence.

Features

  • Directory and URL audits return scores, checks, and ordered gaps.
  • Artifact generation returns text without deploying a service.
  • JSON output supports scripts through audit --json.
  • Configuration shares product facts across generated artifacts.

Runtime surfaces

The library exports auditTarget, formatAuditReport, scoreAuditChecks, defineConfig, defaultConfig, and generator functions. Run the library on Node.js; auditing uses filesystem APIs.

CLI commandBehavior
audit [target]Defaults to .; --json emits the report
initCreates AGENTS.md, server.json, and auth.md; --force permits overwrites
gen <artifact>Prints text; --out writes a file
mcpStarts the stdio server

The six artifact names are agents-md, server-json, offer, agents-route, auth-md, and poppy. agents-route accepts --framework static or --framework next.

Start the standalone server with npx aigentify-mcp. Its two tools are audit with { target } and gen with { artifact, params }.

Configuration

Create aigentify.config.ts, aigentify.config.js, or aigentify.config.mjs for CLI generation:

ts
import { defineConfig } from 'aigentify';
export default defineConfig({  name: 'Example',  description: 'A product API.',  repository: 'https://example.com',  npmPackage: 'example-product',  offer: { price: 0, priceCurrency: 'USD' },});

Export a default configuration or a named aigentifyConfig. Library and MCP generation accept parameters directly.

Delivery/behavior limits

Scores use weighted heuristics. A perfect score does not guarantee agent compatibility, search ranking, or discovery. The crawler check uses one agent User-Agent; it does not test every crawler. Requests have eight-second timeouts; registry failures can leave discovery evidence inconclusive. Audits fetch text without executing browser JavaScript. Generated files contain defaults and templates that require review. The authentication template describes API-key behavior; it does not implement authentication. The Poppy generator emits discovery-only data, not authenticated agent or API connections. init preserves existing files unless --force is set. It does not deploy them.

Integration guides

Status

Version 0.5.0 is a 0.x release. Interfaces and checks can change. Use the GitHub issue channel listed on the npm package for support. Public case studies are not yet published in this README.

FAQ

What does aigentify audit?

aigentify audits a local directory or public URL for agent-readiness signals. Its report contains a score, checks, and actionable gaps.

Which integrations are verified?

aigentify implements Wikidata, npm, and Official MCP Registry probes in source. This rewrite checked the implementation, without a live credential-based verification campaign.

Does aigentify provide a managed service?

aigentify runs in your Node.js process or stdio MCP server. You publish and host the generated artifacts yourself.

How is aigentify different from Lighthouse?

aigentify checks agent-facing discovery and generates artifact text. Lighthouse audits web page quality.

How is aigentify different from axe-core?

aigentify checks agent readiness and public discovery files. axe-core evaluates accessibility in HTML-based interfaces.

Does aigentify need API keys?

aigentify uses no API keys for directory audits or its public registry probes. Generated authentication guides are templates for your product.

Does a score of 100 guarantee compatibility?

aigentify scores implemented heuristics, not end-to-end compatibility with every agent. Test your published interfaces with the clients you support.

Can aigentify fix my website automatically?

aigentify generates text and starter files. You review product facts, implement missing behavior, and deploy the changes.

License

MIT.

來源:README.md,提交 822a4d9

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v0.1.2最新Sep 16, 2026

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