VWAP child-order schedule for a ticker: a qty (default 100) sliced along the intraday U-curve volume profile. Call this when the user wants an order worked in line with typical intraday volume; use twap_plan for even time-slicing and cost_estimate for expected cost.
| Name | Required | Description | Default |
|---|---|---|---|
| qty | No | ||
| 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 disclosure burden. It reveals the tool produces a schedule and uses a U-curve volume profile, but does not explicitly state whether it only generates a plan (no order submission) or any side effects. This is a notable gap for a trading-related tool, though the term 'schedule' implies a non-executing planning function.
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, no fluff, front-loaded with the tool's core function and followed by usage guidance. Every phrase adds value, making it highly concise and well-structured.
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 is simple (2 parameters) and the description covers what it does and when to use it. However, there is no output schema, and the description only vaguely mentions a 'schedule' without detailing the return format (e.g., order intervals, structure). Despite this, the context is adequate for selection and basic invocation.
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 50% (ticker has a minimal description, qty has none). The description enriches qty by clarifying it is the total quantity to be sliced (default 100) and ties it to the U-curve profile, adding meaning beyond the schema's numeric bounds. Ticker is self-explanatory as a path parameter.
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 VWAP child-order schedule generator for a ticker, explaining that it slices a quantity along the intraday U-curve volume profile. It also distinguishes itself from sibling tools like twap_plan and cost_estimate, making its purpose unambiguous.
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 guidance is provided: use this tool when the user wants an order worked in line with typical intraday volume, and alternatives (twap_plan for even time-slicing, cost_estimate for expected cost) are named. This meets the highest bar for usage clarity.
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.
