Daily evening FX market summary article. Call this when the user asks for an end-of-day FX wrap-up or a morning briefing needs an overnight FX recap; optional date_range filter (today/last7days). 600s cache.
| Name | Required | Description | Default |
|---|---|---|---|
| date_range | 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 discloses that the tool returns an article summary and mentions a 600s cache, which is useful behavioral context. However, it does not describe the response format, potential limitations, or whether any filtering/order is applied, leaving some ambiguity.
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 compact (two sentences) and front-loaded: it opens with the core function, then provides usage scenarios, parameter hints, and cache behavior. Every sentence adds value with no redundancy or 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 simple read-only news digest with one optional parameter and no output schema, the description covers the essential aspects: what it does, when to use it, and parameter options. It lacks explicit return field details, but the phrase 'summary article' gives a reasonable expectation. It is more complete than many comparable tool descriptions.
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 description coverage is 0%, but the description compensates by explaining the parameter: 'optional date_range filter (today/last7days)'. This gives meaningful guidance on accepted values and the parameter's purpose, though it does not specify the default behavior when omitted or the exact format.
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 states it provides a 'Daily evening FX market summary article', which clearly identifies the resource and function. It distinguishes itself from sibling tools by emphasizing the end-of-day/nightly angle (e.g., 'sundown', 'end-of-day FX wrap-up', 'overnight FX recap'), though it does not explicitly name alternative 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 trigger scenarios: 'when the user asks for an end-of-day FX wrap-up or a morning briefing needs an overnight FX recap'. This is clear, practical context. However, it does not state when NOT to use this tool or mention alternatives like tengu_v3_news_forex_summary or tengu_v3_news_sundown.
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.
