Zambo AI Tools

zambo_ask

Ask any natural language question about the Zambo Stack — products, APIs, pricing, routing, how-to, use cases, or deep scan mode. Returns a precise structured answer optimized for AI agents. Best for: 'What does ZAMBRO do?', 'Which product should I use for lead generation?', 'How do I call the LeadSignal API?', 'What does Zambo Pass include?', 'How does ZAMBRO deep scan work?'. 20 calls/day free, no auth, no signup.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`q`	Yes	Your question about zambo.dev or any of its 100+ tools across 2 MCPs. Also accepts: question, ask. Examples: 'What is ZAMBRO?', 'How does Zambo Pass work?', 'What is ZAMBOT Swarm Debate?', 'What endpoints are free?'

TDQS

A3.9/5.0

Behavior3/5

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

With no annotations, the description carries full burden. It states the return type ('precise structured answer optimized for AI agents') and rate limits, but lacks details on behavior for out-of-scope questions or response format specifics.

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 a single paragraph that front-loads the purpose and includes examples. It is concise with no superfluous content, though slightly more structured formatting could improve readability.

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 one parameter, no output schema, and numerous sibling tools, the description adequately explains what the tool does, when to use it, and its limitations (rate limit, no auth). It could provide more details on the response structure.

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?

The only parameter 'q' is well-documented in the schema (maxLength, examples, aliases). The description adds context about targeting zambo.dev tools but does not significantly enhance beyond the schema, which has 100% coverage.

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: answering natural language questions about the Zambo Stack. It lists specific topics (products, APIs, pricing, etc.) and provides example queries, distinguishing it from sibling tools like zambo_check or zambo_help.

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 includes a 'Best for' section with example questions and mentions the free tier (20 calls/day). However, it does not explicitly state when not to use this tool versus its 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

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