Zambo AI Tools

bill_audit

Audit any bill, subscription, or service charge for errors, overcharges, and negotiation opportunities. Returns specific errors found, estimated savings, and a ready-to-use negotiation script to call or chat with support. Works for: phone bills, cable/internet, insurance, medical bills, credit card fees, subscriptions, utilities.

Input Schema

TableJSON Schema

Name	Required	Description
`amount`	No	Current monthly amount if not in description.
`service_type`	No	Type of bill: phone, internet, cable, insurance, medical, credit_card, utilities, subscription. Auto-detected if omitted.
`account_length`	No	How long you've been a customer. Loyalty is negotiating leverage. E.g. '3 years', '8 months'.
`bill_description`	Yes	Describe your bill or paste the line items. E.g. 'AT&T bill $180/mo, was $130 six months ago. I've been a customer 5 years.' Or paste actual line items.

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations, description discloses that the tool returns errors, estimated savings, and a negotiation script. It does not mention side effects or state changes, but the read-only nature is implied.

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?

Two sentences: first covers action and outputs, second lists applicable bill types. No fluff, 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?

Tool has 4 parameters, no output schema, no annotations. Description covers core behavior, supported types, and parameter tips. Could mention if any prerequisites (e.g., user account), but fairly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. Description adds value by noting auto-detection for service_type, explaining 'account_length' as leverage, and encouraging pasting line items.

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?

Description clearly states it audits bills for errors, overcharges, and negotiation opportunities, and lists specific return items (errors, savings, script). It distinguishes from sibling audit tools by focusing on financial bills and subscriptions.

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?

Description explicitly lists supported bill types (phone, cable, insurance, etc.), implying when to use. It does not explicitly contrast with other audit tools or state when not to use, but the scope is clear.

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.

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