Paged listing of the full covered ticker universe, filterable to S&P 500 membership or one sector (limit/page paging). Call it when the user wants all the stocks in a sector or an index-membership list to feed a screen.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| limit | No | ||
| sector | No | ||
| is_sp500 | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosing behavior. It mentions paging and filters, but does not describe the return format, field contents, pagination semantics (e.g., max limit, default page), or any potential rate limits or auth requirements. It is adequate but not rich in behavioral detail.
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 exactly two sentences with no wasted words. It front-loads the core function and then provides a clear use-case signal. The structure is ideal for quick agent comprehension.
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 that there is no output schema and no annotations, the description could be more complete about what fields each listed ticker includes, how pagination behaves, and what filters combine. It covers the basics well but leaves some gaps for a tool that is meant to feed a screen.
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. It effectively explains the meaning of all four parameters: 'limit/page paging' covers page and limit, 'S&P 500 membership' covers is_sp500, and 'one sector' covers sector. This adds semantic beyond the bare schema, though it does not detail specific accepted values or defaults.
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 identifies the tool as a paged listing of the full covered ticker universe with filters for S&P 500 membership or sector. It uses a specific verb ('listing') and resource ('ticker universe'), and the mention of filters distinguishes it from related tools like screeners or single-ticker lookups.
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 guidance explicitly states when to call the tool: 'when the user wants all the stocks in a sector or an index-membership list to feed a screen.' It provides clear context but does not explicitly mention when not to use it or name alternative tools, which keeps it slightly below a perfect score.
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.
