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Zambo AI Tools

by dev.zambo

provibe_audit

AI code audit for any public GitHub repository. Returns Provibe Score (0–100), security vulnerability list, dead code map, and an actionable execution plan. Free teaser gives score + top 3 issues. Full audit: $49 one-time OR included in Zambo Pass ($49/mo — 5 audits/month, $245 value). Pass Zambo Pass email in request for full audit. No auth required for teaser.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailNoZambo Pass email for full audit (optional — without it you get the free teaser: score + top 3 issues). Get pass: https://zambo.dev/#zambo-pass
repo_urlYesPublic GitHub repository URL. Example: https://github.com/owner/my-saas
vibe_contextNoOptional context: language, framework, specific concerns, or what the project does

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description covers key behavioral traits: cost model, auth requirements, output composition. It doesn't mention rate limits or side effects, but as a read-only audit, that's 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 information-dense but well-structured, starting with purpose and then details. Could be slightly more concise (e.g., combine pricing lines), but no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite no output schema, the description enumerates all return items (score, vulnerabilities, dead code, plan). For a single-purpose audit tool, this is 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 context beyond parameter descriptions: explains the role of email in triggering full audit, and provides pricing details that help the agent decide when to include it.

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 performs an AI code audit on public GitHub repos, listing specific outputs (Provibe Score, vulnerabilities, dead code map, execution plan). This distinguishes it from siblings, many of which deal with agents, trading, or presence.

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?

It explains free vs. paid versions, how to access full audit via Zambo Pass email, and that no auth is needed for teaser. However, it doesn't explicitly state when not to use or compare to alternatives like 'ghost_audit_report' 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