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Zambo AI Tools

by dev.zambo

agent_brief

Generate a comprehensive machine-readable structured briefing on any URL, product, company, API, codebase, or topic — optimized for AI agent consumption. Instantly gives any agent expert context on anything. Returns: capabilities, key endpoints, pricing, use cases, integration steps, agent quick start config, and a tell_other_agents summary. Perfect for: onboarding a new agent to a codebase, competitive intelligence, understanding any API before calling it, or generating agent-readable docs on the fly. 5 free/day. Zambo Pass: unlimited.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoOptional specific URL to analyze alongside the topic
depthNo'quick' = concise summary (default) · 'deep' = full analysis with integration steps
focusNoOptional focus area: 'api', 'pricing', 'architecture', 'competitors', 'use_cases'
topicYesWhat to brief on — URL, product name, company, API, codebase, or any topic

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries full burden. It discloses return fields, rate limits, and access tiers. It lacks details on auth requirements or potential side effects, but for a non-destructive read 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?

The description is concise (two main sentences plus a list of return items) and front-loaded with the core action. It is slightly verbose in listing return fields, but overall 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?

The description covers the tool's purpose, inputs, outputs, and usage examples. Given no output schema, it effectively describes return values. It is complete enough for an agent to decide when and how to invoke this tool.

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. The description adds no new information beyond what is already in the schema (e.g., depth, focus descriptions are identical). It does not enhance understanding of parameter behavior or interactions.

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 uses a specific verb 'Generate' and identifies the resource as a 'comprehensive machine-readable structured briefing'. It clearly states the scope (any URL, product, company, etc.) and distinguishes from siblings like 'zambo_brief' by emphasizing AI agent consumption and flexibility.

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 provides explicit use cases (onboarding, competitive intelligence, API understanding) and mentions rate limits. However, it does not state when not to use or suggest alternative tools, which would improve guidance.

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