alternative-data: ETF composition or inverse-lookup. Pass ?etf=SPY for full holdings of an ETF, OR ?ticker=NVDA for every ETF that holds the stock (with weight). At least one is required; when both are passed, etf takes precedence.
| Name | Required | Description | Default |
|---|---|---|---|
| etf | No | ||
| limit | No | ||
| ticker | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It discloses the precedence behavior ('when both are passed, etf takes precedence') and adds output detail ('with weight'), which is beyond the schema. It does not mention return format or side effects, but for a read-only data lookup the key traits are covered.
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?
Two crisp sentences with no redundancy. The description front-loads the purpose ('alternative-data: ETF composition or inverse-lookup') then gives precise parameter instructions. Every sentence earns its place.
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 has two modes and three parameters, and the description covers both modes, the required condition, and the precedence. Since there is no output schema, the description partially explains outputs ('full holdings', 'with weight') but does not give a detailed return structure. For a lookup tool, this is adequate but not exhaustive.
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 coverage is 0%, so the description compensates by explaining etf and ticker with concrete examples and their purposes. The limit parameter is left to the schema, but its default and min/max are self-explanatory. The precedence rule further clarifies the relationship between etf and ticker.
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 states the tool's function: 'ETF composition or inverse-lookup' and explains both modes with concrete examples (?etf=SPY and ?ticker=NVDA). This distinguishes it from sibling tools like tengu_v3_intel_etf_summary by specifying full holdings vs holding lookups.
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?
Provides explicit usage instructions for each parameter mode and states the requirement 'At least one is required' along with precedence behavior. However, it does not explicitly compare against alternatives like the ETF summary tool or state when not to use this tool, so it lacks a small part of usage guidance.
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.
