Skip to main content
Glama

Dali by Lulu

by io.github.Lulu-The-Narwhal
OverviewDiscussionsAdmin

score_creative_from_view

Read-only

Score an ad creative YOU are looking at (e.g. a pasted/attached image) against the winning corpus — no URL needed. Use this when the user shares an image in the conversation: read the creative yourself and fill in what you see, and Dali scores it against what wins in the category (3,800+ proven winners), returning the conversion verdict and exactly which winning attributes it's missing.

You (the model) provide the visual read; Dali provides the winning-data scoring. (For a fetchable image URL, prefer score_creative — it adds the embedding similarity headline, which needs the real pixels.)

Fill these from looking at the image: category — vertical: beauty, wellness, supplements, fitness, food, apparel, tech, pets lighting — warm lighting | natural light | studio light | dramatic lighting | clinical bright | dark moody | neon subject — single person | group | product only | no person | before after subject_age — young adult | middle age | senior | child | none format — ugc selfie | testimonial | product hero | lifestyle | chart infographic | text meme | comparison text_density — none | light | heavy dominant_emotion — calm | excited | trust | fear | aspiration | neutral eye_contact — true if a person looks at camera offer_visible — true if a price/discount/offer is shown defects — list any generation defects (extra fingers, garbled text, warped anatomy); [] if clean

Returns: conversion_score (0-100), verdict, matched (winning attributes it has), missing (high-lift attributes to add, each with a fix sentence), has_defect/defects.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNo
defectsNo
subjectNo
categoryYes
lightingNo
eye_contactNo
subject_ageNo
text_densityNo
offer_visibleNo
dominant_emotionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the tool is known to be read-only. The description adds behavioral context: the model must visually inspect the image and fill parameters, and Dali scores against winners. It also describes the output. No contradictions, but no mention of rate limits or prerequisites, so a 4 is appropriate.

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?

The description is well-structured: first paragraph for purpose, second for parameters, third for output. However, it is somewhat lengthy; each sentence is justified given the complexity, but it could be slightly more concise. Still, it's front-loaded with key information.

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?

Given the tool has 10 parameters and the description explains all of them plus the output, it is fairly complete. However, there is a slight inconsistency: the description says defects should be '[] if clean' but schema default is null. Also, it doesn't specify if all parameters must be filled or what happens with defaults. Still, it provides enough for an agent to use.

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?

The input schema has 0% coverage (no descriptions in schema), but the description provides detailed meanings and allowed values for each parameter (e.g., category: 'vertical: beauty, wellness, supplements, fitness, food, apparel, tech, pets'). This fully compensates for the lack of schema descriptions.

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's purpose: 'Score an ad creative YOU are looking at... against the winning corpus'. It specifies the action (score), resource (ad creative), and method (by filling in visual attributes). It also distinguishes itself from the sibling tool 'score_creative' by noting that the sibling is for fetchable URLs.

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 usage guidance is provided: 'Use this when the user shares an image in the conversation' and 'For a fetchable image URL, prefer score_creative'. This clearly indicates when to use this tool versus alternatives.

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

All Dali by Lulu toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources