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Zambo AI Tools

by dev.zambo

trading_propose

Full automated trade proposal workflow: loads your strategy, runs the pure-math risk gate, captures live market context, logs to your private journal, and sends a formatted proposal to your Telegram with ✅/❌ approval buttons. You approve every trade in Telegram — nothing executes without your tap. Paper mode (default): simulates fills, logs results, tracks win rate, counts toward the 20-trade threshold for live unlock. Live mode: after 20 paper trades + explicit enable, proposals include real on-chain tx data for approval. CALL FORMAT: trading_propose({strategy_id: 'strat_abc123', signal: 'RSI crossed below 30 on 15m chart. Volume 3x avg. Price at support.', portfolio_value_usd: 2500, confidence: 0.87, telegram_chat_id: 123456789, email: 'you@example.com'})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailNoYour email for journal tracking.
tokenNoToken/pair override (e.g. 'SOL', 'ETH/USDC'). Defaults to strategy's asset list.
signalYesWhat triggered this trade proposal. Be specific: indicator values, price levels, news catalyst, on-chain signal, etc.
directionNoTrade direction. Default: 'long'.
confidenceNoYour confidence in this signal (0–1). Must meet strategy threshold. Default: 0.82.
strategy_idYesThe strategy_id from trading_strategy_compile.
telegram_chat_idNoYour Telegram chat ID for approval buttons. Get it by messaging @zambodev_bot and typing /chatid.
proposed_size_usdNoOverride position size. Defaults to max_position_pct * portfolio_value_usd.
portfolio_value_usdNoCurrent portfolio value in USD. Used for risk gate math. Default: 1000.

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral transparency. It discloses the workflow steps, approval requirement, paper vs live modes, and the 20-trade threshold. It does not cover error handling or rate limits, but overall provides good insight into tool behavior.

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?

The description is verbose and includes a full call format example that is somewhat redundant with the schema. It front-loads the purpose effectively, but could be more concise by trimming redundant details.

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 the complexity of 9 parameters and no output schema, the description is reasonably complete. It explains the workflow, modes, approval process, and parameter usage. It does not describe return values, but that is partially mitigated by the absence of an output schema.

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. The description adds significant value by providing a concrete call format example and explaining each parameter's role in context, such as the signal parameter requiring specifics. This goes beyond the schema's descriptions.

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 outlines the tool's purpose as a full automated trade proposal workflow, specifying each step (loads strategy, risk gate, market context, journal, Telegram approval). It distinguishes itself from sibling trading tools like trading_strategy_compile and trading_journal by combining all steps into one proposal flow.

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?

The description explains when to use the tool (for trade proposals with Telegram approval) and describes paper vs live modes with a clear unlock condition. However, it does not explicitly state when not to use it or mention alternative tools.

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