Copy-Pasteable cURL Command Generation Prompt Template

This prompt is designed for API documentation engineers and developer relations teams who need to produce ready-to-run cURL examples directly from endpoint specifications. The primary job-to-be-done is transforming an OpenAPI snippet, a route definition, or a plain-text description of an API call into a syntactically correct, shell-safe cURL command that a developer can copy, paste, and execute with minimal friction. The ideal user is a technical writer or platform engineer who understands the API contract but wants to automate the repetitive, error-prone work of formatting headers, escaping payloads, and ensuring cross-platform compatibility across bash, zsh, and Windows shells.

Use this prompt when you have a stable endpoint definition and need to generate examples for API references, quickstart guides, or integration tutorials. It is particularly valuable when you must produce dozens of consistent examples across multiple endpoints, methods, and authentication patterns. The prompt expects structured inputs such as the HTTP method, base URL, path, query parameters, request body schema, and authentication type. It works best when you provide an [OUTPUT_SCHEMA] that specifies the expected success response, so the generated command can include a comment showing what the developer should see. Do not use this prompt for generating examples in SDKs or client libraries—those require idiomatic language patterns, not raw HTTP commands. Avoid it for endpoints with complex multi-step authentication flows like OAuth with PKCE, where a single cURL command cannot capture the full token retrieval sequence.

Before relying on this prompt in a documentation pipeline, implement validation checks for shell safety, placeholder clarity, and cross-platform compatibility. Every generated command must be tested in a sandbox environment against the live API to confirm it produces the expected response. For high-risk or revenue-affecting endpoints, require human review of the generated examples before publication. The next step after adopting this prompt is to wire it into a documentation generation harness that feeds it structured endpoint data and validates the output against a regression test suite.

This section provides the core prompt template for generating copy-pasteable cURL commands. The template is designed to be adapted for different API specifications, documentation styles, and output requirements. It uses square-bracket placeholders that you must replace with your specific context before use. The prompt instructs the model to produce commands that are shell-safe, include proper authentication placeholders, handle payload escaping, and show expected success output.

textCopy
You are an API documentation engineer generating ready-to-run cURL examples from endpoint specifications.

Generate a cURL command for the following API endpoint. The command must be:
- Copy-pasteable into a Unix-like terminal (bash/zsh).
- Shell-safe: properly escape all special characters in URLs and payloads.
- Use [AUTH_PLACEHOLDER] for any authentication token or key.
- Include all required headers specified in the endpoint definition.
- Use a realistic but minimal example payload when a request body is required.
- Show the expected HTTP status code and a truncated example success response body in a comment below the command.
- Use line continuations (backslashes) for readability if the command exceeds 80 characters.

Endpoint specification:
- Method: [HTTP_METHOD]
- URL: [BASE_URL][ENDPOINT_PATH]
- Headers: [HEADERS_LIST]
- Query parameters: [QUERY_PARAMS]
- Request body schema: [REQUEST_BODY_SCHEMA]
- Authentication type: [AUTH_TYPE]

Constraints:
- Do not use hardcoded real credentials.
- Do not use `-k` or `--insecure` flags that disable TLS verification.
- Prefer long-form flags (e.g., `--header` over `-H`) for clarity.
- If the payload contains nested JSON, use a HEREDOC or a separate file reference rather than a single-quoted string to avoid escaping errors.
- For Windows users, add a note that the command is written for Unix shells and may require adaptation for PowerShell or CMD.

Output format:
```bash
# [Brief description of what this command does]
curl --request [METHOD] \
  --url "[FULL_URL]" \
  --header "Authorization: Bearer $API_KEY" \
  --header "Content-Type: application/json" \
  --data '{
    "[KEY]": "[VALUE]"
  }'

# Expected: HTTP [STATUS_CODE]
# {
#   "[RESPONSE_KEY]": "[RESPONSE_VALUE]",
#   ...
# }

Now generate the cURL command for the endpoint specified above.

To adapt this template, replace each square-bracket placeholder with your actual endpoint details. The [AUTH_PLACEHOLDER] should be replaced with the specific token variable name your documentation uses, such as $API_KEY, <YOUR_TOKEN>, or Bearer <token>. If your API does not require a request body, remove the --data flag and the payload section. For APIs with file uploads, replace the JSON payload with --form flags. Always test the generated command in a clean environment before publishing to ensure it executes without shell errors and produces the documented response. For high-risk production endpoints, add a human review step to verify that the command does not expose internal endpoints, hardcoded secrets, or destructive operations without explicit warnings.

This prompt is designed to be called programmatically from a documentation build pipeline, a CI/CD job, or an internal developer portal. The core integration pattern is: fetch an OpenAPI spec or endpoint metadata, hydrate the prompt's [ENDPOINT_SPEC] and [AUTH_SCHEME] placeholders, call the LLM, validate the generated cURL command, and inject the result into your docs site or SDK README. Treat the prompt as a transformation function that converts structured API definitions into executable shell examples.

Validation and safety checks are mandatory before publication. After the model returns a cURL command, run it through a shell syntax validator (e.g., curl --dry-run parsing or a regex-based linter) to catch unescaped characters, missing quotes, or broken line continuations. If the command includes an [AUTH_TOKEN] placeholder, verify it is not a real credential. For high-stakes API surfaces, execute the generated command against a sandbox environment and assert that the HTTP status code and response body shape match the expected success output described in the spec. Log every generation with the input spec hash, model version, and validation result for auditability.

Retry logic and model selection matter. If validation fails, implement a single retry with a more constrained prompt variant that includes the specific validation error (e.g., 'The previous command had an unescaped single quote in the JSON body. Regenerate with proper shell escaping.'). Use a model with strong code-generation performance for this task—GPT-4o or Claude 3.5 Sonnet are appropriate defaults. Avoid smaller or older models that may hallucinate flags or mishandle nested JSON payloads. For bulk generation across many endpoints, batch requests with a concurrency limit to respect rate limits and add a human review step for any command flagged by the validator.

Integrate with your existing toolchain. Store the prompt template in a version-controlled prompts directory alongside your OpenAPI spec. Use a lightweight harness script (Python or Node.js) that reads the spec, iterates over endpoints, calls the LLM, validates outputs, and writes the final cURL examples into your documentation source files. If your docs platform supports shortcodes or partials, render the generated commands as reusable components so they stay synchronized with spec updates. Avoid copying generated commands manually into static docs—this creates drift. Instead, treat the prompt-plus-harness as the source of truth for cURL examples, rebuilt on every spec change.