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Glama
Gatyh
by Gatyh

AI HDRI Generator

generate_hdri
Idempotent

Create 360-degree equirectangular HDRI panoramas and skyboxes from a text prompt. Returns true HDR and an LDR preview for realistic or stylized skies, interiors, and landscapes.

Instructions

360-degree equirectangular HDRI panorama / skybox from a text prompt, true HDR (.hdr) plus an LDR preview image. Realistic or stylized skies, interiors, landscapes. Asynchronous: returns a generation id; poll get_generation. Spends credits (refunded automatically on failure). Typical time: 150 s.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNoOptional, for reproducibility.
promptYesScene, e.g. "golden hour over a misty pine forest, clear sky".
resolutionNo2k = 2048x1024, 4k = 4096x2048, 8k = 8192x4096.4k
max_creditsYesHighest price the user accepted (from quote_generation). The call fails with confirmation_required if missing.
idempotency_keyNoOptional. Same key = same generation, never charged twice. Default: derived from the parameters for 10 minutes; pass a new value to intentionally run the same prompt again.
save_to_libraryNoOptional. When the generation succeeds, publish it in the public 3DTexel community library and add it to the user's library (free). Only if the user asked for it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations cover the safety profile (readOnly=false, destructive=false, idempotent=true, openWorld=true), and the description adds real value on top: async lifecycle, the polling requirement, credit spend with automatic refund on failure, and expected duration. It does not, however, explain credit cost magnitudes or any rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with what is produced, then async/credit/timing facts in short, dense clauses; every sentence carries information. The telegraphic fragment style ('Realistic or stylized skies, interiors, landscapes.') is efficient but slightly choppy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description supplies the missing return contract (generation id), the required follow-up call (get_generation), cost behavior including refunds, and timing. Together with the fully documented 6-parameter schema, an agent has everything needed to invoke and follow through correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents seed, prompt, resolution, max_credits, idempotency_key and save_to_library. The description only reiterates the credit spend, adding no format or syntax detail beyond the schema — the baseline 3 for a fully-covered schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('360-degree equirectangular HDRI panorama / skybox from a text prompt'), plus the outputs produced (true HDR .hdr plus LDR preview). This clearly separates it from siblings like generate_texture and generate_pbr_material without needing their schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives clear operational context: asynchronous, returns a generation id, poll get_generation, credits spent and refunded on failure, ~150 s runtime. It names the follow-up sibling explicitly but never states when to choose an HDRI over the other generators, so selection guidance is implied rather than spelled out.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.