Zambo AI Tools

meme_forge

Generate a meme image — scene + overlaid caption text — as a shareable image URL. Describe the visual scene and the top/bottom text you want on the meme. Returns a direct image URL that renders inline. Use when user says 'make a meme', 'generate a meme about X', or wants a funny captioned image.

Input Schema

TableJSON Schema

Name	Required	Description
`style`	No	Visual style: classic (impact font feel), modern, dark, wholesome. Default: classic.
`concept`	Yes	What the meme image should look like. E.g. 'dog sitting at a desk looking stressed at a computer'
`top_text`	No	Text for the top of the meme. Optional.
`bottom_text`	No	Text for the bottom of the meme. The punchline. Optional.

TDQS

A3.8/5.0

Behavior2/5

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

No annotations provided, so description carries full burden. It discloses output is a direct image URL but omits retention policies, rate limits, permissions, or whether the meme is stored. Minimal behavioral context.

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?

Three well-structured sentences: core function, parameter guidance, and usage triggers. No superfluous information; highly concise.

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?

For a meme generator with no output schema and basic parameters, the description covers key aspects. It could add size limits or URL expiry, but overall it's adequate given tool simplicity.

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 coverage is 100% with clear descriptions for each parameter. The description reiterates 'scene and top/bottom text' but adds no new meaning beyond the schema. Baseline 3 is appropriate.

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 it generates a meme image with overlaid caption text as a shareable URL. It distinguishes itself from sibling tools like 'image_generate' by focusing on meme format with text overlays.

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?

Description explicitly lists trigger phrases ('make a meme', 'generate a meme about X') but does not mention when to avoid using it or provide alternatives like 'image_generate' for non-meme images.

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

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TDQS

A3.5/5.0

Disambiguation3/5

Many tools have distinct purposes, but there are several overlapping or redundant tools (e.g., leadsignal vs leadsignal_generate, multiple code audit tools, multiple trading proposal/journal tools, and several 'universal' entry points like zambo_help, zambo_ask, zambo_universal). Descriptions help, but the volume creates ambiguity.

Naming Consistency3/5

Naming conventions vary across prefixes (zambo_, zambot_, axis_, presence_, trading_, etc.), with some tools using single words (weather, translate) and others using verb_noun patterns. Aliases like leadsignal_generate for leadsignal break consistency. While prefixes provide some grouping, the overall pattern is mixed.

Tool Count2/5

125 tools is excessive for a single MCP server, even if the server aims to be a universal stack. This makes it overwhelming for agents to navigate and increases the likelihood of misselection. Many tools could be split into domain-specific servers.

Completeness5/5

The tool surface is extraordinarily comprehensive, covering agent identity, cross-layer orchestration, code analysis, content generation, legal scanning, lead generation, trading, on-chain data, and more. Nearly any common agent task is supported with multiple tools, leaving few obvious gaps.

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