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zambo_watch

Set a persistent async watcher — Zambo monitors any condition in the background and sends a Telegram alert when it fires. This is the ONLY MCP tool that works while you sleep. Claude sets the watch and moves on — you get pinged when it happens. Examples: 'watch ETH and alert me when it hits $3000', 'alert me when Anthropic releases a new model', 'watch my competitor site and ping me when their pricing changes', 'notify me when Bitcoin dominance drops below 50%'. Checks every 30 minutes via live web search + AI condition evaluation. Requires notify_telegram (Telegram username like @yourname or chat ID) or notify_email. Use zambo_watch when the user says: watch, monitor, alert me when, ping me when, notify me when, keep an eye on.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetYesWhat to watch. E.g. 'ETH price', 'Anthropic news', 'competitor.com pricing page', 'Bitcoin dominance'
conditionYesThe condition that should trigger the alert. E.g. 'price hits $3000', 'new model released', 'pricing changes', 'drops below 50%'
notify_emailNoEmail address to receive the alert (if no Telegram)
notify_telegramNoTelegram username (e.g. '@yourname') or numeric chat ID to receive the alert

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations provided, the description fully covers behavioral traits: it's persistent, async, checks every 30 minutes via live web search and AI evaluation, and sends Telegram/email alerts. It also notes that Claude sets and moves on, implying no further action needed.

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 well-structured with a clear opening sentence, followed by examples and usage guidelines. It is moderately concise, but some repetition (e.g., multiple examples) could be trimmed. Overall, it effectively conveys key information without excessive verbosity.

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 no annotations, the description adequately explains the tool's behavior (async, periodic checks, alert delivery). It lacks details on how to manage or cancel watchers, but for a watch tool, this is acceptable. The description provides sufficient context for an AI agent to decide when and how to use it.

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 examples for 'target' and 'condition'. However, it says 'Requires notify_telegram... or notify_email' while the schema does not require these parameters, creating a potential inconsistency. This reduces clarity about parameter requirements.

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's purpose: setting a persistent async watcher that monitors conditions and sends alerts. It provides specific verb+resource ('Set a persistent async watcher') and distinguishes itself as the only tool that works asynchronously. Examples further clarify the purpose.

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?

The description explicitly tells when to use the tool: 'Use zambo_watch when the user says: watch, monitor, alert me when, ping me when, notify me when, keep an eye on.' It also mentions periodic checking (every 30 minutes) and required notification methods, providing clear context for use.

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