Overall market-wide news-sentiment rollup over a date_range (default last7days). Call this when the user asks how the market 'feels' right now or whether the news backdrop is bullish or bearish — before drilling into single tickers.
| Name | Required | Description | Default |
|---|---|---|---|
| date_range | No | last7days |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the disclosure burden. It communicates the rollup nature and default window, but does not elaborate on the response structure, data sources, or whether it aggregates only certain asset classes. The description is functional but lacks depth in disclosing the tool's operational behavior beyond its purpose.
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, front-loaded with the core functionality, and then supplies usage guidance. Every clause earns its place, with no wasted words or redundancy.
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 and no output schema, the description gives sufficient context for selection and invocation. It clearly identifies when to use it and the general nature of the result. The only missing piece is an explicit description of the return payload, but the term 'rollup' implies a summary, making this a minor gap.
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 single parameter date_range appears in the description with its default, but the schema already declares the default. With 0% schema description coverage, the description adds no additional meaning about valid formats or allowed values. It provides minimal context (that the parameter controls the lookback period) but does not go beyond what the schema shows.
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 a specific verb and resource: an 'overall market-wide news-sentiment rollup' over a date range. It distinguishes itself from sibling tools by emphasizing 'market-wide' and the 'before drilling into single tickers' guidance, making the scope 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?
Explicit when-to-use context is provided: 'Call this when the user asks how the market feels right now or whether the news backdrop is bullish or bearish.' It also gives an exclusion/directional cue with 'before drilling into single tickers,' which helps an agent decide between this and more granular sentiment 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.
