SSE stream of live per-venue bid/ask quote events for the requested symbols (bid/ask price+size + per-side venue IDs). Connecting auto-subscribes coverage within ~5s. Quiet outside US market hours — that is correct, not broken. Sizes are the venue's numbers untransformed; never present them as share counts.
| Name | Required | Description | Default |
|---|---|---|---|
| symbols | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It goes beyond the basics by explaining the auto-subscription behavior, normal quiet periods, and a critical data caveat that sizes are untransformed venue numbers and must not be presented as share counts. This is rich, honest behavioral disclosure.
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, front-loaded with the main purpose, and all additional sentences add critical context (auto-subscription, quiet hours, data interpretation warning). No fluff 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?
The description covers the essential behavioral aspects (USB subscription, quiet hours) and the data contents (bid/ask price+size, venue IDs), which is substantial for a simple stream tool with no output schema. However, it lacks details on the symbols parameter format, which is a minor completeness gap given the tool's simplicity.
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 has one parameter 'symbols' with no description (0% coverage). The description only says 'for the requested symbols', which is nearly a tautology and does not clarify the expected format (e.g., comma-separated list, single symbol, case sensitivity). This is a significant gap for correct invocation.
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 an SSE stream of live per-venue bid/ask quote events with bid/ask price+size and per-side venue IDs. The specific verb 'stream' and resource 'per-venue bid/ask quote events' distinguishes it from sibling stream tools like ticks, bars, and signals.
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 provides clear context on when to expect data: auto-subscribes within ~5s and quiet outside US market hours, with reassurance that quiet is correct. However, it does not explicitly name alternatives or exclusions, though the distinct data type makes it obvious.
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.
