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OpenAPI-Spezifikation aus aufgezeichnetem API-Traffic bootstrap…

Nutzt mitmproxy2swagger, um aufgezeichnete mitmproxy-Flows oder HAR-Exporte in ein erstes OpenAPI-Dokument zu verwandeln, das ein Agent verfeinern, validieren und an nachgelagerte Tools übergeben kann.

Was ist OpenAPI-Spezifikation aus aufgezeichnetem API-Traffic bootstrap…?

Diese Fähigkeit ermöglicht es einem KI-Agenten, aus aufgezeichnetem API-Traffic (wie mitmproxy-Flows oder HAR-Exporten aus Browser-DevTools) automatisch eine erste OpenAPI-Spezifikation zu generieren. Sie ist besonders nützlich, wenn eine API bereits existiert, aber kein formaler Vertrag (OpenAPI-Dokument) vorliegt, der für die Client-Generierung, das Mocking, Tests oder dokumentierte APIs benötigt wird. Der Agent nutzt das Tool `mitmproxy2swagger`, um die Verkehrsdaten zu analysieren und eine erste Spezifikation zu erstellen, die dann manuell oder automatisiert verfeinert und validiert werden kann. Die Fähigkeit unterstützt verschiedene Installationsmethoden (pip, git, Docker) und erfordert grundlegende Python-Kenntnisse. Nach der Erstellung kann die Spezifikation in CI/CD-Pipelines integriert oder an andere Tools zur weiteren Verarbeitung übergeben werden.

Funktioniert mit~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/bootstrap-openapi-spec-from-captured-api-traffic-before-client-or-test-automation
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Dokumentation

OpenAPI-Spezifikation aus aufgezeichnetem API-Traffic bootstrappen (vor Client- oder Testautomatisierung)

Nutzt mitmproxy2swagger, um aufgezeichnete mitmproxy-Flows oder HAR-Exporte in ein erstes OpenAPI-Dokument zu verwandeln, das ein Agent verfeinern, validieren und an nachgelagerte Tools übergeben kann. Verwenden Sie es, wenn die API bereits existiert, aber kein Vertrag vorliegt, und Sie eine konkrete Spezifikation benötigen, bevor Sie Clients, Mocks, Tests oder überprüfbare Dokumentation generieren.

Voraussetzungen

Python 3 und pip, sowie mitmproxy-Flow-Aufzeichnungen oder ein HAR-Export aus den Browser-DevTools

Installation

Verwenden Sie die für Ihre Umgebung passende Installations- oder Einrichtungsmethode:

  • $ pip install mitmproxy2swagger
  • $ git clone [email protected]:alufers/mitmproxy2swagger.git
  • $ docker build -t mitmproxy2swagger .
  • $ docker run -it -v $PWD:/app mitmproxy2swagger mitmproxy2swagger -i <pfad_zu_mitmproxy_flow> -o <pfad_zu_ausgabe_schema> -p <api_präfix>

Anforderungen und Hinweise des Upstream-Projekts:

  • poetry für das Abhängigkeitsmanagement

Grundlegende Nutzung oder Einstiegsnotizen:

Dokumentation

Quelle

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

Academic Paper Citation Network Mapper

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ACF Custom Fields REST Exposer

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ACF Extended for Advanced Custom Fields Workflows

An ASE skill built around ACF Extended, the WordPress enhancement suite for Advanced Custom Fields that adds field types, admin improvements, front-end forms, options pages, and developer tooling. It is a practical fit for agents working inside complex WordPress content models and custom field workflows.

ACF to Gutenberg Block Migrator

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act Local GitHub Actions Runner

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Use AgentClick when an agent should pause before risky commands, plans, drafts, or code changes so a human can inspect, edit, approve, or reject them in a purpose-built browser UI.

Add Claude design-system and accessibility workflows with UX/UI

Use UX/UI Agent Skills when Claude should generate tokens, component specs, accessibility audits, and framework-specific UI code from a repeatable design workflow.

Add executable smoke tests for shell scripts and CLIs before ref

Use Bats-core when an agent needs to turn fragile shell scripts or command-line workflows into something it can verify repeatedly after edits. The agent writes focused Bash tests for success paths, failure paths, and output contracts, then runs them locally or in CI before a refactor, release, or incident fix goes out.

Add graph-backed memory and context retrieval to agent workflows

Use Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.

Add IDE-style semantic code navigation and symbol-safe refactors

Give a coding agent symbol-aware lookup, cross-file rename, and structural edit tools before it starts making brittle text-only changes.

Add managed long-term memory to LangGraph agents with LangMem

Give LangGraph agents memory management and search tools so they can store, retrieve, and update durable facts across sessions.

Add multimodal lifelong memory to MCP and Python agents with Sim

Use SimpleMem to store, compress, index, and retrieve text or multimodal memories for agents through MCP or Python integrations.

Add persistent project memory and hook-driven synthesis with Cla

Keep Claude Code sessions grounded in prior decisions, project context, and daily handoff notes instead of starting from zero every time.

Add Postgres-native vector retrieval to agent and RAG workflows

Store embeddings beside application data in Postgres, create vector indexes, and query nearest neighbors for semantic search, RAG, recommendations, or agent memory retrieval.

Address GitHub PR review comments from the current branch with g

Find the open PR for the current branch, gather unresolved review comments, and drive a focused comment-resolution workflow with gh-authenticated context.

Add runtime guardrails to TypeScript agents with VoltAgent

Use VoltAgent to intercept, validate, and enforce input/output policies in TypeScript agent workflows.

Add temporal context memory to agent workflows with Zep

Use Zep as an external context layer for agents that need to store events, assemble temporal graph context, and retrieve relevant memory before model calls.

Adobe Firefly API Batch Image Generator

Calls Adobe Firefly

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