Skip to main content
Glama

Get Model Details (OpenRouter)

pixara_get_model_details
Read-onlyIdempotent

Check per-provider pricing, supported parameters, and passthrough options for an OpenRouter image model to avoid failed image generation calls.

Instructions

Get per-provider pricing, supported parameters, and passthrough options for one OpenRouter image model.

This is a read-only, no-cost call. Use it before pixara_generate_image / pixara_edit_image to confirm exactly which parameters a model/provider supports and what it costs — unsupported parameters are silently ignored or rejected by the API, so checking first avoids wasted/failed calls.

Args:

  • model (string, required): OpenRouter model slug, e.g. 'black-forest-labs/flux.2-pro'.

  • response_format ('markdown'|'json', default 'markdown').

Returns: Per-provider breakdown: pricing (billable type, unit, price, tier/variant), supported parameter descriptors (enum values, numeric ranges, or plain booleans), and any allowed_passthrough_parameters for use with the generate/edit tools' provider_options field.

Examples:

  • Use when: "How much does flux.2-pro cost and what steps/guidance params does it take?"

  • Use when: "Does gpt-image-1 support transparent backgrounds on this provider?"

  • Don't use when: browsing across many models (use pixara_list_image_models instead)

Error Handling:

  • "Resource not found" / empty endpoints -> the model id may be wrong; verify with pixara_list_image_models

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYesOpenRouter model slug to inspect, e.g. 'openai/gpt-image-1'.
response_formatNoOutput format: 'markdown' for humans or 'json' for machine processing.markdown
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint. The description adds that the call is 'no-cost' and explains that unsupported parameters are silently ignored or rejected, justifying why checking first is important. No contradictions.

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

Conciseness5/5

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

The description is well-structured with clear sections (main description, args, returns, examples, error handling). It is front-loaded with the primary purpose and every sentence adds meaningful information without redundancy.

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?

Even without an output schema, the description details the return structure (per-provider pricing, parameter descriptors, passthrough options). It also covers error scenarios. All aspects of the tool's usage are covered comprehensively.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds example model slugs and clarifies the response_format options with practical examples ('markdown' for humans, 'json' for machines), adding value beyond the 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?

The description clearly states the tool retrieves per-provider pricing, supported parameters, and passthrough options for a single OpenRouter model. It uses specific verbs ('Get', 'confirm') and distinguishes itself from sibling tools like pixara_generate_image, pixara_edit_image, and pixara_list_image_models.

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

Usage Guidelines5/5

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

Explicit guidance: use before generate/edit to avoid wasted calls, and avoid when browsing many models (suggesting pixara_list_image_models). Provides example use cases and error handling instructions.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/pinkpixel-dev/pixara-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server