Daily options volume and put/call ratio per day for one ticker from the options-flow feed (default 30 days). Call this when the user asks whether options activity or put/call skew is elevated versus recent days, or how bullish/bearish the options tape has been trending.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| ticker | Yes | Path parameter 'ticker' (required). |
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 usefully discloses the data source ('options-flow feed'), granularity ('per day'), and default lookback ('default 30 days'). However, it does not describe the response structure, pagination, or any caveats about historical data availability, leaving some transparency gaps for a tool with no output 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 two sentences, front-loaded with the tool's core function followed by usage guidance. Every word earns its place, with no filler 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?
Given no output schema and no annotations, the description covers purpose, source, default lookback, and when to use. It could be more explicit about return format, but the first sentence already implies a daily series. It is sufficiently complete for a straightforward options data endpoint.
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 low (only ticker is described as a path parameter). The description adds that the data is per-day with a default 30-day window, implying the limit parameter controls the number of days, and 'per day' clarifies the output granularity. This partially compensates for the sparse schema but does not explicitly define limit's semantics beyond the default.
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 provides 'daily options volume and put/call ratio per day for one ticker from the options-flow feed.' It identifies the resource and scope well, distinguishing it from sibling options tools like options_chain or options_flow by focusing on volume/ratio daily series for a single ticker. However, it lacks an explicit verb like 'retrieves' or 'returns,' so it falls just short of a 5.
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 explicitly says 'Call this when the user asks whether options activity or put/call skew is elevated versus recent days, or how bullish/bearish the options tape has been trending.' This provides clear triggering context. It does not name alternatives or exclusions, but the guidance is sufficiently specific to guide tool selection.
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.
