Skip to main content
Glama

nanoodle

by io.github.nanoodlecom
OverviewDiscussionsAdmin

image-model-arena

Compare four image models on the same useful brief. Run makes four paid images. Judge exact text, object count, composition and color before choosing the model for your own task. Each contender alr… text:Shared test brief -> image:Contender 1 -> image:Contender 2 -> image:Contender 3 -> image:Contender 4; returns image (muse-image/text-to-image, 1:1) + image (turbo, 1k) + image (grok-imagine-image/v2.0/text-to-image, 1:1) + image (recraft-v4, 1024×1024) saved to disk (file paths in result). Runs on NanoGPT — $0.59 deposit per call, paid in Nano (XNO) — settles at actual model cost + 20%, change returned; no account needed; last run $0.2455, ~1m 39s. Example: Reviewed sample (https://nanoodle.com/examples/gallery/#image-model-arena). The same bicycle-repair poster brief sent to four image models. All four retained the requested text in this run; only Grok rendered recognizable tire levers. Compare all outputs before choosing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
_payment_idNoPayment id from this tool's previous payment-required response. Phase 3 only: after /x402/watch closes with status paid, call again with the same arguments plus this id to open the RESULTS stream. Do not pass it while payment is still pending — monitor the watch SSE first.
Shared_test_briefNoText; default: "Create a square poster for a bicycle repair workshop. Exact heading: FIX A FLAT. Exact footer: SATURDAY 10 AM. A sing..."; optional

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / Shared_test_brief
      Added value: +{
+  "description": "Text; default: \"Create a square poster for a bicycle repair workshop. Exact heading: FIX A FLAT. Exact footer: SATURDAY 10 AM. A sing...\"; optional",
+  "type": "string"
+}
    • removedInput schema / properties / Text
      Removed value: -{
-  "description": "default: \"Liziba, Chongqing at 11:47pm: Light Rail Line 2 frozen mid-crossing through the 6th–8th floors of a lived-in resident...\"; optional",
-  "type": "string"
-}
  2. Changed1 schema field changed
    • changedInput schema / properties / Text / description
      Previous value: -"default: \"a tiny dragon curled up asleep in a teacup, macro photo, soft morning light\"; optional"New value: +"default: \"Liziba, Chongqing at 11:47pm: Light Rail Line 2 frozen mid-crossing through the 6th–8th floors of a lived-in resident...\"; optional"
  3. First observed

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of disclosing behavior. It clearly states that the run creates four paid images, outlines the deposit and cost model, mentions the results stream, and says images are saved to disk with file paths in the result. This is transparent about cost and output behavior.

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

Conciseness3/5

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

The description is informative but somewhat verbose and repetitive, repeating 'paid' and 'compare' multiple times. It includes example and pricing details that may be useful but could be tightened without losing meaning.

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

Completeness4/5

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

Despite no output schema, the description adequately explains the workflow, the four returned images, the saved-file behavior, cost details, and how to handle the payment-id parameter. It is complete enough for an agent to understand the tool's purpose and execution flow.

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

Parameters5/5

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

Schema coverage is 100% and the description adds substantial meaning: it explains the _payment_id lifecycle across payment phases and provides the full default text for Shared_test_brief. This goes well beyond the raw 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 identifies the tool as comparing four image models on a shared brief, which distinguishes it from sibling tools that generate or edit images. It also states the intended use: judge outputs before choosing a model for your own task.

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?

The description provides practical guidance on when to use the tool and what to do with the results: compare all outputs, judge text, object count, composition, and color, then choose a model. It also explains the payment flow and the role of _payment_id. It does not explicitly contrast with sibling tools, but the use case is clear.

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

All nanoodle toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources