Index hedge proposals (SPY/QQQ/IWM) computed from live dealer positioning — protective puts when dealers are short gamma and IV rank is cheap, collars when the 25-delta risk reversal shows calls rich, plus IV term-structure context
| Name | Required | Description | Default |
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the computation source ('live dealer positioning'), the strategy triggers, and that the output includes 'IV term-structure context.' It does not mention side effects or return format in detail, but the read-only, proposal-generation nature is evident from the wording.
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 a single dense sentence that front-loads the core purpose ('Index hedge proposals') and then efficiently explains the logic. Every clause adds meaningful information: indices, dealer positioning, protective put conditions, collar conditions, and term-structure context. 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 parameters, the description provides a fairly complete picture: it names the indices, explains the inputs ('live dealer positioning'), and gives concrete examples of generated proposals. It could be more explicit about the response structure, but the low complexity and zero-parameter design make this sufficient.
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 tool has zero parameters, so there is nothing for the description to add beyond what the schema already shows. Baseline for 0 parameters is 4; no parameter semantics are needed.
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 produces 'Index hedge proposals (SPY/QQQ/IWM)' computed from 'live dealer positioning,' giving a specific verb+resource scope. It distinguishes itself from sibling tools by focusing on hedging and options-based strategy logic rather than generic data retrieval or analytics.
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 for when the tool's outputs apply: 'protective puts when dealers are short gamma and IV rank is cheap' and 'collars when the 25-delta risk reversal shows calls rich.' It does not explicitly name alternatives or exclusions, but the conditions and index scope imply the appropriate use case.
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.
