Category-scoped news feed: section=general for market-wide or alltickers for company-tagged stories, filterable by topic, sector, industry, and source. Call this when the user wants themed or sector-level news rather than coverage of a specific ticker.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| items | No | ||
| topic | No | ||
| sector | No | ||
| source | No | ||
| section | No | general | |
| industry | No | ||
| date_range | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the disclosure burden. It explains the behavior of the section parameter (general vs alltickers) and lists filter dimensions (topic, sector, industry, source), which adds value beyond the schema. It does not mention return format or pagination details, but the core scoping behavior is 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, front-loaded with the core definition and section modes. The second sentence gives usage guidance without redundancy. Every part 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?
Given the large number of news-related siblings, the description differentiates this tool from ticker-specific news retrieval. It could more explicitly contrast with other category/topic news tools like tengu_v3_news_by_topic, but the scoping and usage guidance are sufficient for selection.
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%, but the description adds meaning for section, topic, sector, industry, and source by explaining their roles. It clarifies the enum values for section and the filtering intent. Page, items, and date_range are not mentioned, but the schema provides defaults and types.
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 defines the tool as a 'Category-scoped news feed' and explains the two section modes ('general for market-wide or alltickers for company-tagged stories'). It explicitly contrasts with 'coverage of a specific ticker', distinguishing it from ticker-specific news 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?
Provides an explicit usage directive: 'Call this when the user wants themed or sector-level news rather than coverage of a specific ticker.' This gives clear context and exclusion, though it does not name specific alternative tools like tengu_v3_news_ticker_news.
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.
