Daily off-exchange (dark pool + ATS) volume for one ticker from the alternative-data feed (default 30 days). Call this when the user asks how much of a stock's volume trades off-exchange or how dark-pool share is trending; use tengu_v3_intel_darkpool_ticker for individual prints.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| ticker | Yes | Path parameter 'ticker' (required). | |
| freshness | No | off |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden. It discloses data frequency ('daily'), source ('alternative-data feed'), and default range ('default 30 days'). However, it does not describe the output format (e.g., whether it's a time series, what fields are included) or the effect of the 'freshness' parameter on behavior. This is adequate but not fully transparent.
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?
Two concise sentences front-load the core purpose and immediately follow with usage guidance. There is no filler or redundant information; every phrase adds value.
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 is useful but incomplete for a data-retrieval tool with no output schema. It does not specify what the return value looks like (e.g., a list of daily volumes, with percentages), nor does it explain the 'freshness' options. Given the tool's moderate complexity (3 params, no output schema), the description covers the main use case but leaves key details for the agent to infer.
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 only 33%, and the description compensates partially by clarifying that 'limit' corresponds to a number of days (default 30). The 'freshness' parameter is left unexplained in both the schema and description, leaving a gap. The 'ticker' parameter is trivially described in the schema as required, and the description's mention of 'one ticker' adds no extra meaning.
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 off-exchange (dark pool + ATS) volume for a single ticker, with a default 30-day lookback. It distinguishes itself from the sibling tengu_v3_intel_darkpool_ticker by specifying that this tool is for aggregate off-exchange/trend data, not individual prints.
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?
Explicit when-to-use guidance is provided: 'Call this when the user asks how much of a stock's volume trades off-exchange or how dark-pool share is trending.' It also names an alternative tool (tengu_v3_intel_darkpool_ticker) for individual prints, giving clear usage boundaries.
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.
