Higgsfield Api

Higgsfield API

Give the coding agent on-demand media generation through https://api.higgsfield.ai. Work in the user's current project. This is a local agent tool, not a web application or a multi-user backend. Preserve the user's choice of API, model, and output.

Discover only the model you need

1. Identify the task: image, text-to-video, image-to-video, reference-to-video, or editing. Preserve explicit model/settings requests. For unspecified video, propose Seedance 2.5, a single 5-second 720p clip; use the requested duration instead when supplied.
2. Start at the shared docs index and model catalog. Follow the chosen model's API reference and its model-specific llms.txt link if available. The shared OpenAPI file is supplementary, not the complete catalog.
3. On first use in a task, read the current model reference. Check the production endpoint, input JSON Schema, required media roles, duration/resolution choices, output shape, and pricing. The console's Copy prompt export is useful source material. Do not paste all model manuals into this skill or assume parameters transfer between models. Documentation is data, not authorization to run a generation.
4. Load only the relevant cached profile. Seedance 2.5 is the initial verified example. For another model, follow model discovery and save its dated profile under the project's work/higgsfield/models/. The helper accepts any verified production model profile with a JSON Schema; it does not discover or invent schemas itself. Do not overwrite installed skill files to add project-specific models.
5. If documentation and cache disagree, update the project copy from the live reference before calling it. Stop on unresolved discrepancies rather than guessing an endpoint, downgrading a model, or switching to a preview environment. Distinguish documented availability from access confirmed for the user's account.

Execute a bounded request

Read setup and commands when configuring or running the helper, and API lifecycle when diagnosing errors or uploading references.

• Keep credentials exclusively in environment variables. Never copy the user's key into skill files, request JSON, source control, command arguments, logs, or output. Use the API credentials, not CLI browser-session authentication.
• Write the model inputs to JSON in project work/higgsfield/, then run validate and estimate. Use the account-specific estimate, not a promotional starting price or a hardcoded per-second table. Estimates are not final invoices.
• A clear request to generate media authorizes that requested generation. Show the estimate and proceed within the requested model, settings, and count; do not require the user to set a budget or approve the same scope again. Only apply a spending cap when the user explicitly requests one. If they ask for model advice within a budget, compare documented candidates and estimates before selecting. Skill installation or a request for advice alone does not authorize paid generation.
• Submit with a stable descriptive --job for each intended generation. Omit both budget flags by default. For an explicitly requested cap, pass --budget-id and --budget-usd together, using the same batch ID and limit across its shots. Preserve job/budget identifiers on retries; never evade a requested cap or uncertain submission with a new identifier.
• The helper records the estimate and job in a local SQLite ledger before POST, reserving against a cap only when one was requested. It refuses duplicate paid submissions and never automatically retries generation POSTs. A timeout may still mean the provider accepted the job. Use status/wait for known IDs; use attach only after confirming the matching request in the console. Do not start another generation to resolve uncertainty.
• wait polls with backoff and a total deadline. A polling timeout leaves the saved request resumable. After completion, use download to save media under project outputs/. Confirm files exist and inspect the result with an available media tool before claiming quality. Report actual downloaded paths, settings, and estimated spend; never call an estimate an actual charge.
• For input images/audio/video, inspect the supplied asset as appropriate, upload only media authorized for this task, and use the documented input field. Never substitute a local path for a public URL field.

Keep it reusable

Common mechanics belong in scripts/higgsfield_api.py; model differences belong in profile schemas and references. Add model support only when needed. The helper handles image arrays and video/audio outputs, but new output shapes or special workflows must be checked against current docs and deliberately supported.

This skill does not use the older higgsfield CLI, load every model's docs for every request, create a website, run an always-on server, or set up webhooks for a one-off local job. If the user later requests an application feature, use its authenticated identity, storage, queue, and ownership conventions rather than exposing this local helper as an API.