Skill: xxmzdxxxm/falimagegen (version 1.0.0)

--- name: fal-image-gen description: "Call fal.ai model APIs for image generation (text-to-image and image-to-image). Use when a user asks to integrate fal, construct requests, run jobs, handle auth, or return image URLs from fal model APIs." --- # Fal Image Gen ## Overview Use this skill to implement text-to-image or image-to-image calls against fal model APIs. Prioritize correctness by checking the current docs for the selected model’s required inputs/outputs and authentication requirements. ## Quick Start 1. Identify the target model ID from the fal model API docs. 2. Collect inputs from the user. - Text-to-image: `prompt`, optional `negative_prompt`, size/aspect, steps, seed, safety options. - Image-to-image: source image URL, strength/denoise, plus prompt/options above. 3. Pick the calling method. - If the user prefers SDKs: provide Python and/or JavaScript examples. - If the user prefers REST: provide a curl/HTTP example. 4. Execute the request and return image URL(s) from the response. ## Workflow: Text-to-Image 1. Resolve the model ID and schema. - Open the fal model API docs and confirm the exact input fields and output format. 2. Validate inputs. - Ensure prompt is non-empty and size/aspect settings are supported by the model. 3. Build the request. - SDK: call the SDK’s `run`/`submit` method with an `input` object. - REST: call the model endpoint with a JSON body that matches the schema. 4. Execute and parse output. - Extract image URL(s) from the response fields defined by the model. 5. Return URLs. - Provide a clean list of URLs and note any metadata the user asked for (seed, size, etc.). ## Workflow: Image-to-Image 1. Resolve the model ID and schema. 2. Validate inputs. - Ensure the source image is reachable by URL (or converted to the required format). - Confirm any strength/denoise range constraints from docs. 3. Build the request. - Include source image + prompt + other options as required by the model. 4. Execute and parse output. - Extract image URL(s) from the response fields defined by the model. 5. Return URLs. ## SDK vs REST Guidance - Prefer SDKs for simpler auth and retries. - Prefer REST when the user needs raw HTTP examples, or when running in environments without SDK support. - Never hardcode API keys. Follow the docs for the required environment variable or header name. ## Minimal Examples (Fill From Docs) Use these as templates only. Replace placeholders after checking the docs. ### Python (SDK) ```python # Pseudocode: replace with the exact fal SDK import + call pattern from docs import os # from fal import client # or the current SDK import MODEL_ID = "<model-id-from-docs>" input_data = { "prompt": "a cinematic photo of a red fox", # "image_url": "https://..." # for image-to-image # "negative_prompt": "...", # "width": 1024, # "height": 1024, } # result = client.run(MODEL_ID, input=input_data) # urls = extract_urls(result) ``` ### JavaScript (SDK) ```javascript // Pseudocode: replace with the exact fal SDK import + call pattern from docs // import { client } from "@fal-ai/client"; const MODEL_ID = "<model-id-from-docs>"; const input = { prompt: "a cinematic photo of a red fox", // image_url: "https://..." // for image-to-image }; // const result = await client.run(MODEL_ID, { input }); // const urls = extractUrls(result); ``` ### REST (curl) ```bash # Pseudocode: replace endpoint, headers, and payload schema from docs curl -X POST "https://<fal-api-base>/<model-endpoint>" \ -H "Authorization: Bearer <API_KEY>" \ -H "Content-Type: application/json" \ -d '{ "prompt": "a cinematic photo of a red fox" }' ``` ## Resources - `references/fal-model-api-checklist.md`: Checklist for gathering inputs and validating responses. - `references/fal-model-examples.md`: Example templates for text-to-image, image-to-image, and REST usage.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)