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Central Command — x402 Trading Intelligence

by io.github.tlefko

Macroeconomic Event Calendar

cc.economic_calendar
Read-onlyIdempotent

Call cc.economic_calendar — Upcoming high-impact macroeconomic events (CPI, FOMC, NFP, etc.) with forecast vs previous values. 60-min cache. Purpose: Upcoming high-impact macroeconomic events (CPI, FOMC, NFP, etc.) with forecast vs previous values. 60-min cache. Behavior: READ-ONLY. Does not place orders, move funds, or mutate your exchange account. Responses may be cached (~3600s). 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: Array of events with dates, countries, impact level, forecast/actual/previous values. 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: macro, calendar, fomc, cpi, nfp, economic.

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?

Beyond the annotations (readOnlyHint, idempotentHint), the description discloses caching (~3600s), authentication requirements (X-Api-Key or x402), HTTP 402 behavior for anonymous calls, cost per successful call, rate limits, and explicitly states 'READ-ONLY' with no side effects on exchange accounts. This is substantial behavioral context that annotations alone do not provide.

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 labeled sections (Purpose, Behavior, Auth, Cost, Rate limit, Returns, Guidelines, Tags), making it scannable. However, the Purpose section repeats the opening sentence nearly verbatim, and the cache duration is mentioned twice (60-min cache and ~3600s), adding minor redundancy. Still, every major section earns its place.

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 has a simple schema, an output schema, and clear annotations, the description is comprehensive: it covers purpose, behavior, auth, cost, rate limit, return structure, and usage guidelines. An agent can confidently select and invoke this tool without needing additional undocumented context.

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 schema already covers the only parameter (__x_payment) with a detailed description, so baseline is 3. The tool description adds meaning by explaining the parameter's role in x402 payment proof, clarifying it is not a business parameter but a billing/payment mechanism, and tying it to auth and HTTP 402 handling. This goes beyond schema-only semantics.

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 opens with a specific verb 'Call' and clearly identifies the resource: 'Upcoming high-impact macroeconomic events (CPI, FOMC, NFP, etc.) with forecast vs previous values.' It also names concrete examples and contrasts with other data sources via tags, clearly distinguishing it from sibling tools like market news or funding rates.

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 the tool ('Use for research / signal context') and when not to rely on it alone ('Do not invent fills from this data alone'). It also names a specific sibling, cc.agent_strategy, as the recommended paper-trading companion before live orders, providing clear alternative usage.

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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