Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· Developer Tools
falimagegen
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.
skill openclawclawhub Free
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.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, agents/openai.yaml, references/fal-model-examples.md, references/fal-model-api-checklist.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
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New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
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I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- xxmzdxxxm
- Source page
- View original listing
- Canonical URL
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Documentation
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 modelβs required inputs/outputs and authentication requirements.
Quick Start
Identify the target model ID from the fal model API docs. 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. 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. Execute the request and return image URL(s) from the response.
Workflow: Text-to-Image
Resolve the model ID and schema. Open the fal model API docs and confirm the exact input fields and output format. Validate inputs. Ensure prompt is non-empty and size/aspect settings are supported by the model. Build the request. SDK: call the SDKβs run/submit method with an input object. REST: call the model endpoint with a JSON body that matches the schema. Execute and parse output. Extract image URL(s) from the response fields defined by the model. Return URLs. Provide a clean list of URLs and note any metadata the user asked for (seed, size, etc.).
Workflow: Image-to-Image
Resolve the model ID and schema. Validate inputs. Ensure the source image is reachable by URL (or converted to the required format). Confirm any strength/denoise range constraints from docs. Build the request. Include source image + prompt + other options as required by the model. Execute and parse output. Extract image URL(s) from the response fields defined by the model. 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)
# 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)
// 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)
# 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.
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
3 Docs1 Config
- SKILL.md
- references/fal-model-api-checklist.md
- references/fal-model-examples.md
- agents/openai.yaml