Portfolio VaR and CVaR at a chosen horizon and confidence (defaults: 1-day, 99%). Call it when the user asks 'how much could the portfolio lose?' or needs a tail-risk number before sizing or hedging decisions.
| Name | Required | Description | Default |
|---|---|---|---|
| confidence | No | ||
| horizon_days | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full transparency burden. It explains the core output (VaR/CVaR) and defaults but does not disclose return format, methodology, or what portfolio data is used. The description does not contradict any annotations and is harmless but lacks depth on behavior.
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 the core purpose and defaults front-loaded, followed by one sentence of usage guidance. Every word earns its place; no fluff.
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?
For a simple tool with two optional params and no output schema, the description covers purpose, defaults, and a usage signal. It does not explain the output format or whether a portfolio is pre-configured, but those are minor gaps given the tool's simplicity and the extensive sibling list.
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?
The schema description coverage is 0%, so the description must clarify the parameters. It does so by mapping 'horizon' to horizon_days, 'confidence' to confidence, and stating defaults (1-day, 99%). This gives additional context beyond the raw names, though it stops short of describing ranges or interpretation.
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 provides portfolio VaR and CVaR with configurable horizon and confidence, giving concrete defaults. It includes a specific call signal ('how much could the portfolio lose?') that distinguishes it from the broad sibling list. The verb is implied but the resource and output metric are unambiguous.
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?
The description explicitly states when to invoke the tool ('when the user asks "how much could the portfolio lose?" or needs a tail-risk number before sizing or hedging decisions'), providing clear context. It does not mention alternatives or exclusions, but the guidance is direct and actionable.
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.
