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Central Command — x402 Trading Intelligence

by io.github.tlefko

Traditional Markets Dashboard

cc.traditional_markets
Read-onlyIdempotent

Call cc.traditional_markets — Live quotes for S&P 500, Nasdaq, Dow, VIX, Gold, Oil, US Bonds, DXY, and major forex pairs. 15-min cache. Purpose: Live quotes for S&P 500, Nasdaq, Dow, VIX, Gold, Oil, US Bonds, DXY, and major forex pairs. 15-min cache. Behavior: READ-ONLY. Does not place orders, move funds, or mutate your exchange account. Responses may be cached (~900s). Auth: X-Api-Key or x402 payment proof (X-PAYMENT / __x_payment). Anonymous unauthenticated calls receive HTTP 402 with payment accepts. Cost: $0.001 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: 60/min (per API key). Tier: standard. Returns: Multi-category quotes: indices, metals, energy, bonds, forex with price and change percentages. Guidelines: Use for research / signal context. Pair with cc.agent_strategy (paper) before any live order. Do not invent fills from this data alone. Tags: tradfi, spx, nasdaq, gold, dxy, vix, correlation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
__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.

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

A4.8/5.0
Behavior5/5

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

The description adds substantial behavioral context beyond the annotations: it explicitly states READ-ONLY, does not mutate account, notes caching (~900s), details auth methods (X-Api-Key, x402), rate limits, billing cost, and that billing is not a side effect. This fully discloses behavior and operational constraints.

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 clear labeled sections (Behavior, Auth, Cost, Rate limit, Returns, Guidelines). However, it repeats the same purpose sentence twice ('Call cc.traditional_markets — Live quotes...' and 'Purpose: Live quotes...'), which is redundant. Otherwise, the formatting is excellent and front-loaded.

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?

Given the tool's simplicity (no required params, simple data fetch), the description is exceptionally complete. It covers usage, auth, cost, rate limits, return content, and integration with other tools. An output schema exists, so return structure is further documented. No critical gaps.

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?

The input schema already describes the single optional parameter __x_payment with high clarity. The description additionally explains its context in the auth flow (x402 payment proof, retry after HTTP 402), reinforcing its purpose beyond the schema. Since schema coverage is 100%, this extra context earns a 4.

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 explicitly states the tool provides live quotes for a specific set of traditional market instruments (S&P 500, Nasdaq, Dow, VIX, etc.). This is a specific verb+resource+scope that clearly distinguishes it from sibling tools focused on crypto or other data. No ambiguity.

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 'Guidelines' section explicitly states when to use it ('research / signal context'), recommends pairing with cc.agent_strategy (paper) before live orders, and warns not to invent fills from this data alone. This provides clear when/when-not guidance and names an alternative/complementary tool.

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

A3.7/5.0
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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