Recent FX news with sentiment for one or more currency pairs: title, source, sentiment (Positive/Neutral/Negative), date, topic tags. PRIMARY tool for pair-specific drilling (EUR-USD, GBP-USD, USD-JPY, AUD-USD) — call when the user asks what's moving a specific pair; use by_category for macro themes. 180s cache.
| Name | Required | Description | Default |
|---|---|---|---|
| items | No | ||
| pairs | Yes | ||
| date_range | No | today |
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 discloses the '180s cache' behavior, which is a valuable non-obvious trait. It also clarifies the scope (pair-specific news with sentiment). While it doesn't mention read-only status or error behavior, the cache disclosure adds meaningful transparency beyond the schema.
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 concise, with three sentences each serving a distinct purpose: defining the output, giving usage guidance, and noting cache behavior. There is no redundant or filler content.
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?
Since there is no output schema, the description's enumeration of returned fields (title, source, sentiment, date, topic tags) helps complete the picture. It also covers usage guidance and cache. However, parameter semantics are incomplete, but the tool is simple enough that the missing explanations are minor.
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 description coverage is 0%, so the description must compensate. However, it only partially explains the 'pairs' parameter ('one or more currency pairs') and does not clarify 'items' or 'date_range'. The enum values in the schema are self-explanatory, but the description fails to add any meaning to these parameters, leaving a significant gap.
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's function: 'Recent FX news with sentiment for one or more currency pairs' and lists the returned fields. It also distinguishes the tool from siblings by declaring it 'PRIMARY tool for pair-specific drilling' and specifically naming the alternative 'by_category' for macro themes.
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 when the user asks what's moving a specific pair', and contrasts it with the alternative 'use by_category for macro themes'. This provides clear direction on selecting this over related 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.
