Zambo AI Tools

zambo_remember

Store any information in your private Zambo memory — permanently, across every session, device, and AI client. Claude loses all context between sessions. zambo_remember fixes that forever. Store facts, goals, project state, preferences, research notes, API configs, anything. Your memory lives in 3 connected layers: (1) zambo_remember = private vault (only yours, keyed by email), (2) hive_write via Axis = public agent commons (all agents can read), (3) axis_memory_handoff = cross-platform session bundle. Free: 20 memories per email. Zambo Pass: unlimited.

Input Schema

TableJSON Schema

Name	Required	Description
`key`	Yes	Memory key — short label for recall. Examples: 'project_goal', 'api_config', 'daily_priority', 'client_name'
`email`	Yes	Your email — namespaces this memory to you privately
`value`	Yes	What to remember. Can be any text — plain notes, JSON configs, markdown, anything.

TDQS

A4.4/5.0

Behavior4/5

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

No annotations provided, so description carries full burden. Discloses permanence, cross-session persistence, privacy via email namespace, and storage limits. However, lacks details on overwrite behavior (e.g., if key exists, does it update?) and success/failure response. Still above average.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is over 100 words with promotional language ('Claude loses all context... fixes that forever'). While core info is front-loaded, the layer comparison and tier details add verbosity. Could be more concise without losing essential guidance.

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 no output schema and simple storage operation (3 params), description covers purpose, usage, and constraints. Explains privacy model, limits, and alternatives. Lacks mention of idempotency or response format, but acceptable for a straightforward store tool.

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 has 100% coverage with clear descriptions. Description adds value beyond schema by explaining email namespaces memory privately, providing examples for key (e.g., 'project_goal', 'api_config'), and stating value accepts plain text, JSON, markdown. Baseline 3 elevated due to added context.

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 'Store any information in your private Zambo memory' with specific verb and resource. Explicitly distinguishes from sibling tools by explaining three memory layers: private vault (zambo_remember), public commons (hive_write), and cross-platform bundle (axis_memory_handoff).

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

Usage Guidelines5/5

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

Provides explicit when-to-use (private storage) and alternatives: 'hive_write via Axis = public agent commons' and 'axis_memory_handoff = cross-platform session bundle'. Also mentions free tier limit (20 memories) and Zambo Pass for unlimited, guiding usage constraints.

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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