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Zambo AI Tools

by dev.zambo

fridge_forge

Turn whatever is in your fridge into a real dinner plan. Give it a list of ingredients you have on hand and it returns 3 complete recipes with step-by-step instructions, cook time, difficulty, and a short shopping list for anything you're missing. Works for any dietary preference — vegetarian, vegan, keto, gluten-free, whatever. Free, unlimited. Perfect for: 'what can I cook tonight?', 'I have eggs and pasta', 'use up leftover chicken'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
vibeNoOptional cooking vibe: 'quick' (under 20 min), 'comfort food', 'healthy', 'fancy', 'spicy'. Default: practical and quick.
dietaryNoOptional dietary restrictions: 'vegetarian', 'vegan', 'keto', 'gluten-free', 'dairy-free', 'halal', etc.
servingsNoNumber of people eating. Default: 2.
ingredientsYesIngredients you have on hand. e.g. 'eggs, cheddar, spinach, leftover pasta, half an onion, milk'

TDQS

A4.1/5.0
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses that the tool generates 3 recipes with step-by-step instructions, cook time, difficulty, and a shopping list, and that it is free and unlimited. However, it does not mention whether it modifies any data or has side effects, but given it is a generation tool, this is acceptable.

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?

Description is concise (3 sentences) and front-loaded with the core action. It efficiently covers purpose, output, and examples without unnecessary words.

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 moderate complexity (4 params, no output schema), description adequately explains the output format (3 recipes with details) and usage scenarios. Lacks only depth on edge cases but sufficient for most agents.

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 baseline is 3. Description adds value by providing example input for ingredients and context for optional parameters like vibe and dietary, but does not significantly extend beyond 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?

Description uses specific verb ('turn whatever is in your fridge into a real dinner plan') and resource, clearly stating it returns 3 complete recipes. Distinguishes from sibling tools like meal_plan by focusing on ingredient-based generation and specific output details.

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?

Provides clear context with example use cases ('what can I cook tonight?', 'I have eggs and pasta') and mentions dietary preferences. However, does not explicitly state when not to use this tool or mention alternatives among siblings.

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.

Resources