Pre-trade expected execution cost for a ticker: spread, market impact, and commission for a given qty (default 100) and side (buy/sell). Call it to know what a trade will actually cost before sizing or routing it; use twap_plan/vwap_plan for the execution schedule itself.
| Name | Required | Description | Default |
|---|---|---|---|
| qty | No | ||
| side | No | buy | |
| ticker | Yes | Path parameter 'ticker' (required). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the tool produces an estimate (not a guarantee), names the cost components, and implies a read-only, pre-trade nature. It could add context about data sources or units, but for a simple estimator this is adequate. It does not contradict anything.
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 sentences, front-loaded with the core purpose, followed by a usage tip. No filler, every clause adds value. This is a model of concise, structured description.
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 tool has no output schema, so the description must convey return value and workflow context. It lists the three cost components (spread, impact, commission) and states when to call it ('before sizing or routing'). It doesn't specify units or return format, which would be nice, but for its simplicity the coverage is strong. It also complements the execution-plan siblings.
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 only 33% (only ticker has a description). The description compensates by explaining qty (default 100) and side (buy/sell), including defaults and the meaning of the side parameter. It does not add detail on qty bounds beyond defaults, but the schema covers those. The description adds meaningful semantic context beyond the bare schema.
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 computes 'pre-trade expected execution cost' for a ticker, listing specific components: spread, market impact, and commission. This is a specific verb+resource with a clear output scope. It also distinguishes itself from sibling tools twap_plan/vwap_plan, which is exemplary.
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?
Explicitly says 'Call it to know what a trade will actually cost before sizing or routing it' and directs to 'use twap_plan/vwap_plan for the execution schedule itself.' This gives both when-to-use and alternative tools, making the decision boundary crystal clear.
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.
