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Central Command — x402 Trading Intelligence

by io.github.tlefko

Autonomous Trading Agent

cc.squirrel_chat_v2
Destructive

Call cc.squirrel_chat_v2 — Full AI trading assistant powered by GPT that can analyze markets, compute indicators, fetch live data, place orders, manage positions, and provide strategic advice. Purpose: Full AI trading assistant powered by GPT that can analyze markets, compute indicators, fetch live data, place orders, manage positions, and provide strategic advice. Behavior: conversational AI that CAN place/cancel orders and manage positions when the linked account allows it. Treat as potentially destructive. Confirm intent before asking it to trade live. Auth: X-Api-Key required (and linked exchange credentials for execution actions). Cost: $0.03 USDC per successful call (x402 Base USDC pay-per-use or prepaid X-Api-Key balance). Linked Connect keys are free. This is billing, not a side effect. Rate limit: 10/min (per API key). Tier: enterprise. Returns: Conversational AI response with embedded trade execution, market analysis, indicator computations, and chart drawing commands. Guidelines: Prefer paper/simulation paths. For live money require explicit human confirmation (confirm_live / action=execute). Report real HTTP errors; never invent proxy failures. Tags: ai, agent, autonomous, trading, analysis, execution, conversational.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageYesNatural language message to the AI agent Required.
__x_paymentNoOptional x402 payment proof (same value as X-PAYMENT header). Use when retrying after HTTP 402 if your MCP client cannot set custom headers. Not a business parameter. Optional.
conversation_idNoContinue existing conversation Optional.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYesTrue when the gateway HTTP status is 2xx.
dataNoParsed JSON body from the endpoint (shape varies by slug).
errorNoError message when ok is false.
statusYesUpstream HTTP status from x402-gateway.
billingNoOptional payment / cost metadata when present.
endpointYesCatalog slug that was invoked (e.g. funding-rates).

TDQS

A4.3/5.0
Behavior5/5

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

The description goes well beyond the annotations (destructiveHint=true) by detailing that it can place/cancel orders and manage positions, requiring confirmation before live trading. It also discloses auth requirements, cost, rate limits, and a directive to report real HTTP errors, adding rich behavioral context.

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 well-structured with labeled sections (Purpose, Behavior, Auth, Cost, etc.) but contains redundancy: the full capability list is repeated verbatim in both the opening sentence and Purpose section. It is informative but not maximally concise.

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?

This is a complex, potentially destructive tool, and the description covers all essential aspects: purpose, behavior, auth, cost, rate limits, return type, and safety guidelines. With output schema present and detailed annotations, the description is thorough enough for safe and correct invocation.

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 description coverage is 100% for all three parameters, so the schema already fully documents them. The description does not add parameter-specific meaning beyond what the schema provides, so the baseline of 3 applies.

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 is a full AI trading assistant that can analyze markets, compute indicators, fetch live data, place orders, and manage positions. This specific verb+resource framing distinguishes it from sibling data tools and makes its purpose unmistakable.

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 provides clear context for when to use the tool (as a conversational trading agent) and includes explicit safety guidelines like preferring paper/simulation and requiring human confirmation for live money. It does not explicitly name alternative tools or when-not-to-use scenarios, but the context is strong.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Central Command — x402 Trading Intelligence toolsInspect
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TDQS

A3.7/5.0
Disambiguation2/5

Multiple tools have overlapping or unclear boundaries. The AI chat tools cc.squirrel_chat, cc.squirrel_chat_v2, and cc.openclaw_chat all provide conversational trading assistance with near-identical descriptions, while cc.central_signal and cc.external_signal both normalize signals for execution. Additionally, cc.asset_scanner, cc.auto_fetch_market_data, cc.data_tools, and cc.ma_fetch all supply technical indicator data with significant overlap.

Naming Consistency4/5

All tools share the 'cc.' prefix and use snake_case consistently, which creates a uniform feel. However, naming style mixes nouns (cc.asset_scanner, cc.data_tools) with verbs (cc.auto_fetch, cc.list_catalog) and compound forms (cc.strategy_backtest, cc.trade_builder), so it is not a strict verb_noun pattern. Minor deviations keep it from a 5.

Tool Count2/5

With 33 tools, the server is well beyond the typical well-scoped range of 3-15 and even above the 'heavy' 16-25 range. While the trading intelligence domain can be broad, this count feels overstuffed rather than curated, especially given the many overlapping data and AI tools.

Completeness3/5

The core trading workflow is covered: market data, technical analysis, signals, strategy backtesting, paper trading, and live execution all have tools. However, there is no dedicated account management tool (e.g., get_balance, list_positions) and no explicit delete_strategy, with these operations buried inside cc.agent_strategy's action parameter. Notable gaps remain for a complete lifecycle.

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