Detected market-moving events across the market over a lookback window (hours param, default 24). Call this when the user asks 'did anything big happen today?' or wants a scan of recent catalysts market-wide; use tengu_v3_news_latest for headlines on one ticker.
| Name | Required | Description | Default |
|---|---|---|---|
| hours | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden. It discloses the lookback window and default hours, and explains the market-wide scope. However, it doesn't specify what constitutes 'market-moving' or describe the output format, leaving a slight gap in transparency.
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 purpose in the first sentence and usage in the second. Every word earns its place, with no redundant filler.
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 one-parameter tool with no output schema or annotations, the description covers purpose, usage, and parameter semantics sufficiently. It could be more complete by mentioning output type or event selection criteria, but it's adequate for a simple scan tool.
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 description adds minimal semantic value to the 'hours' parameter by labeling it as a 'lookback window' and mentioning the default 24. The schema already provides type, default, min, and max constraints, so the description only slightly enhances understanding of the parameter's purpose.
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 detects market-moving events across the market over a lookback window, which is a specific verb+resource+scope. It also distinguishes itself from the sibling tool tengu_v3_news_latest, which handles headlines for a single ticker.
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?
It explicitly provides when to use the tool with example user queries ('did anything big happen today?') and a clear exclusion/alternative ('use tengu_v3_news_latest for headlines on one ticker'), leaving no ambiguity about selection.
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.
