Zambo

Zambo Universal

zambo_universal

Destructive

Universal Zambo entry point for routing natural-language requests across supported Zambo tools through one MCP connection. Covers strategy, code audits, lead generation, wallet intelligence, provenance certificates, swarm coordination, and live market data. Returns a route, execution state, downstream tool results when available, and receipt information.

Input Schema

TableJSON Schema

Name	Required	Description
`mode`	No	Collaboration mode. execute routes and performs the request; continue uses the current session trail; verify checks whether the current session has completed a request. Default: execute.
`need`	Yes	Natural language description of what you need. Any length. Also accepts: message, query, prompt, input, goal, text. Example: 'How do I protect my AI agent from prompt injection?'
`email`	No	Optional email, only with the user's consent. Namespaces Pass access and a compact working trail so the same user can continue across AI clients without restarting.
`format`	No	Response format. Default: json.
`context`	No	Optional extra context. Supported keys: repo_url, goal, trade, city, wallet, domain. Example: { "repo_url": "https://github.com/owner/repo" }
`remember`	No	Optional explicit fact to persist in this stable session. It is returned by mode:'verify'; only use after the user asks you to remember it or clearly consents.
`session_id`	No	Alias for _session_id. Use one stable ID for the whole conversation so Zambo and the host AI do not repeat completed steps.
`_session_id`	No	Stable ID generated by the host AI once per conversation and reused on every Zambo call. Enables a shared working trail across multi-step tasks.
`session_code`	No	Optional ZAMBO-XXXX handoff code from Telegram /export. Loads that saved conversation into this request so another AI can continue immediately.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`ok`	No
`result`	No
`run_id`	No
`verify`	No
`sources`	No
`executed`	No
`grounding`	No
`understood`	No
`planned_tools`	No
`result_status`	No
`executed_tools`	No
`observed_status`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 26, 2026

TDQS

A3.8/5.0

Behavior3/5

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

Annotations already provide destructiveHint=true, and the description adds that it returns execution state and downstream tool results, implying it can execute downstream tools. It doesn't elaborate on potential side effects or permissions, but the annotation covers the destructive nature; still, some added context on downstream execution would be valuable.

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?

The description is three sentences with no fluff. It front-loads the core purpose in the first sentence, lists domains in the second, and summarizes outputs in the third. Every sentence earns its place.

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 tool with 9 parameters, an output schema, and rich annotations, the description covers purpose, scope, and returns. The main gap is the lack of guidance on when to use this router versus specific siblings, but the output schema and annotations fill most of the remaining context.

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%, and the description adds no parameter-specific information. The description mentions 'natural-language requests' which maps to the 'need' parameter, but this is already clear from the schema; the baseline of 3 applies.

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 is a universal entry point for routing natural-language requests across supported Zambo tools, using specific verbs and resources. It enumerates the domains it covers, which distinguishes it from the specific sibling tools like ghost_audit_report or live_price.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage: it's the universal entry point, so you'd use it when you have a natural-language request and aren't sure which specific tool to call. However, it doesn't explicitly state when to avoid it or when to prefer a sibling tool like leadsignal directly, leaving this to inference.

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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