Forecast regime probabilities N days ahead (default 21-day horizon). Call it when the user asks 'is the regime about to change?' or wants the forward market-state outlook rather than today's label — use tengu_regime for the current read.
| Name | Required | Description | Default |
|---|---|---|---|
| horizon_days | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It clearly states the tool's behavior (forecasting probabilities for a future horizon) and implies that it is a read-only operation via the verb 'forecast.' It also provides the default horizon and explicitly contrasts with the current-read sibling, but does not elaborate on output format or additional behaviors. Still, for a simple forecast tool, the description is adequately transparent.
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 long, front-loaded with the core purpose, and every sentence contributes useful information: the first states what the tool does, the second provides usage guidance and names the alternative. There is no redundant or unnecessary text.
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 tool with one optional parameter, no output schema, and no annotations, the description covers the essentials: what it does, when to use it, and what the parameter means. It also differentiates it from a key sibling. The main minor gap is that it does not describe the exact return shape beyond 'regime probabilities,' but this is sufficient for the tool's simplicity.
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 has 0% description coverage, so the description must compensate. It fully explains the meaning of the sole parameter: 'N days ahead' and provides the default '21-day horizon.' This adds significant semantic value beyond the raw schema (type, min, max, default), making the parameter's purpose and optionality clear.
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 uses a specific verb and resource: 'Forecast regime probabilities N days ahead' with a clear scope (default 21-day horizon). It also explicitly distinguishes itself from the sibling tool tengu_regime, which provides the current label. This makes the tool's purpose unmistakable and differentiates it from related tools.
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 gives explicit when-to-use guidance: 'Call it when the user asks "is the regime about to change?" or wants the forward market-state outlook.' It also names the alternative for the current read: 'use tengu_regime for the current read.' This is exactly the kind of contextual direction an agent needs to choose between the two regime tools.
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.
