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Zambo AI Tools

by dev.zambo

zambo_swarm

Spawn a coordinated multi-agent swarm around any goal in one call. NOT a debate — a division of labor. Zambo assembles specialized agents (researcher, strategist, critic, executor), runs them in parallel, and synthesizes a coordinated output with full provenance showing which specialist contributed what. Makes 'become a coordinated swarm' a one-call capability instead of a framework you have to wire yourself. CALL FORMAT: zambo_swarm({goal: 'your goal'}) — pass roles[] to customize composition, depth='quick' for 2-agent fast mode. Use when you need multi-domain analysis: complex strategy, code + security + UX review, research + execution planning.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalYesWhat the swarm should accomplish. Be specific. E.g. 'Audit this SaaS pricing strategy and propose 3 alternatives with projected impact'.
depthNoquick = 2-agent focused synthesis (fast, ~10s); deep = 4-agent full swarm (thorough, ~25s). Default: deep.
rolesNoOptional: override default specialist roles. Options: researcher, strategist, critic, executor, analyst, coder, security_reviewer. Max 4.

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that the tool runs agents in parallel, synthesizes output with provenance, and is a one-call capability. It does not mention destructive actions or auth needs, but the core behavior is clearly described.

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 fairly concise with each sentence adding value. It front-loads key information (purpose, contrast, behavior) and provides parameter details. Slightly verbose but still efficient.

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's complexity and lack of output schema, the description adequately covers purpose, usage, parameters, and behavioral context. Return values are mentioned ('synthesized output with full provenance'), though could be more detailed. Overall sufficient.

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 significant meaning: it provides a concrete example for 'goal', explains 'depth' options with time estimates, and clarifies 'roles' options and constraints. This goes beyond the schema's basic 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 spawns a coordinated multi-agent swarm, using a specific verb ('Spawn') and resource. It explicitly distinguishes itself from the sibling 'zambot_swarm_debate' by stating 'NOT a debate — a division of labor,' providing clear differentiation.

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 gives explicit usage context: 'Use when you need multi-domain analysis: complex strategy, code + security + UX review, research + execution planning.' It also provides a call format and notes about custom roles, but does not explicitly state when not to use it or mention alternatives beyond the debate contrast.

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