Economic calendar with actual, forecast, and previous values for macro releases (Fed/CPI/NFP/ECB) — these prints are priced-in by FX traders, so call it for any 'what did CPI print / what macro data hit this week' question. Filter by currency (USD/EUR/JPY) and importance (high/medium/low). 600s cache.
| Name | Required | Description | Default |
|---|---|---|---|
| currency | No | ||
| date_range | No | last7days | |
| importance | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral burden. It discloses a 600s cache and the fact that data includes actual/forecast/previous values, but it does not describe the return format, pagination, or any limitations. The cache mention adds useful context, yet key behavioral aspects remain unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no filler. It packs purpose, usage context, filter options, and cache information front-loaded. Every clause contributes value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple (3 optional params, no output schema) and the description covers the core purpose and two filters. However, it misses the date_range parameter and does not explicitly state what the response contains (e.g., a list of events) beyond the values. Given no output schema, the description should have been slightly more explicit about return structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage. The description adds meaning for the 'currency' and 'importance' parameters by listing allowed values (USD/EUR/JPY, high/medium/low), but it omits the 'date_range' parameter entirely. The phrase 'this week' hints at the default range but does not explain the parameter options.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly defines the tool as an economic calendar with actual, forecast, and previous values for macro releases like Fed/CPI/NFP/ECB. It also gives a concrete usage example ('what did CPI print / what macro data hit this week'), which distinguishes it from other news/forex tools in the sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to call it: for any 'what did CPI print / what macro data hit this week' question, and provides filter guidance for currency and importance. However, it does not name alternative tools or explicitly state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
With 336 tools, there is substantial overlap. Over a dozen health/status tools share nearly identical 'is the system healthy?' descriptions (e.g., tengu_status, tengu_ready, tengu_ml_health, tengu_v3_system_health, tengu_v3_stream_status), and multiple single-ticker analysis (tengu_ml_predict, tengu_copilot_score_ticker, tengu_v3_intel_ml_prediction) and top-picks (tengu_copilot_top_picks, tengu_ml_top_picks, tengu_v3_trade_setups) tools have poorly defined boundaries. Agents would frequently misselect.
The server mixes no-version (tengu_crypto), v2 (tengu_v2_drift), v3 (tengu_v3_intel_*), and copilot (tengu_copilot_*) families, and within families there is inconsistent verb/noun ordering (tengu_v3_research_fetch_url vs tengu_v3_news_summary). While subfamilies like tengu_v3_private_markets_* are internally consistent, the overall naming pattern is chaotic and unpredictable.
336 tools is far beyond any reasonable tool set size, even for an all-in-one financial data platform. This extreme count creates choice paralysis, high latency in tool selection, and makes the server effectively unusable for autonomous agents. The calibration guideline marks 50+ as extreme; this is nearly 7x that threshold.
The platform covers a vast domain: equity and crypto prices, fundamentals, insider trading, options, news (including crypto and FX), private markets, streaming data, risk metrics, and execution planning. There are minor gaps (no direct multi-ticker comparison tool, no order placement), but the surface is remarkably comprehensive for an analysis-focused server.
