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Using HELVA CLOUD with LLMs and Coding Agents

Guidance for ChatGPT, Claude, Gemini, Perplexity, Copilot, Cursor, Lovable, and agentic coding tools to use HELVA CLOUD docs and APIs accurately.

Docs status: active draft • Last docs sync: 2026-02-24

Page Summary

Quick Answer

Start agent sessions with /llm.txt, then provide the exact task and the canonical docs pages for that task. Require the agent to label planned endpoints and validate against Errors and Rate Limits before finalising code.

Who this is for

  • - Developers using coding assistants
  • - Founders prototyping with AI tools
  • - Agentic coding workflows

What you can do here

  • - Give agents the correct docs in the correct order
  • - Use prompt templates that reduce incorrect assumptions
  • - Force explicit handling of planned vs live features
  • - Validate generated code before shipping

Code examples on this page

  • - cURL: No
  • - JavaScript/TypeScript: Yes
  • - Python: No
  • - JSON request/response: No
  • - Config snippets: Yes
  • - Status labels: Live, Beta, Planned, Coming soon

Related docs

  • llm.txt - Machine-readable site summary for agents
  • Workflows - Task-based implementation paths
  • API Reference - Request conventions and endpoint docs
Last updated
2026-02-24

Read this first (for agents)

  1. 1. Read /llm.txt to identify HELVA CLOUD purpose, audiences, workflows, and canonical pages.
  2. 2. Read the exact task page in /docs/workflows or /docs/getting-started.
  3. 3. Read /docs/api, /errors, and /rate-limits before generating production integration code.
  4. 4. Treat anything labelled Planned or Coming soon as non-live and generate placeholders only.
Prompt template for coding agents
txtActive draft
You are implementing a HELVA CLOUD integration.
Goal: [describe exact task]
Read first: /llm.txt
Then read: /docs/getting-started, /docs/workflows, /docs/api, /errors, /rate-limits
Rules:
- Use only documented live endpoints.
- If docs label a feature Planned/Beta, mark code and comments clearly.
- Include cURL and TypeScript examples when possible.
- Include error handling and retry/backoff logic.
- List assumptions and unresolved placeholders.
Project context block for Cursor/Lovable
txtActive draft
HELVA CLOUD integration task
- Site purpose: build and tooling layer for AI workflows, app delivery, automation
- Canonical docs: /llm.txt, /docs, /docs/workflows, /docs/api
- Required output: parsable setup steps, env vars, code examples, error handling
- Do not invent endpoints; use Planned placeholders if necessary

Common mistakes to avoid

  • - Assuming a placeholder endpoint is live because an example exists.
  • - Omitting error handling or rate limit retries in generated code.
  • - Hiding configuration values instead of documenting required environment variables.
  • - Using stale docs without checking the changelog date.