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tengu_v3_trade_setups

Top trade setups from the decision engine with defensive-alternates baked in. When the screen is one-sided (>=70% same direction across 3+ picks), the response carries universe_skew = 'bearish' | 'bullish' | 'mixed' AND a regime_warranted_alternative block containing the editorial fallback basket (defensive | cash_heavy | value_tilt | momentum). Each alternative carries strategy label, curated candidates with thesis per name, and a one-sentence rationale. Brain consumes the alternative when the primary picks don't fit the user's risk frame — e.g. all-bearish screen on a long-bias capital-allocation query surfaces the defensive basket so the model never has to refuse or invent. Schema is ADDITIVE — primary setups array unchanged from v2.41.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
min_convictionNo

TDQS

A3.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden of behavioral disclosure. It thoroughly explains the conditional response structure, the contents of the alternative block, and the additive schema promise. It does not explicitly state that the tool is read-only or describe error handling, but the focus on output structure provides substantial transparency beyond a simple 'get setups' statement.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but well-structured, with each sentence adding unique value: purpose, condition for alternatives, structure of alternatives, example use, and schema compatibility. It is longer than ideal but appropriate for the complex conditional behavior it describes. No word is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema and two simple parameters, the description comprehensively covers the conditional response and the alternative basket. However, it leaves a gap by referencing 'v2.41' without explaining what the primary `setups` array contains, which could confuse an agent unfamiliar with that version. It also does not cover parameter effects on the response.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description does not mention `limit` or `min_conviction` at all. While the parameter names are self-explanatory, the description adds no additional context, usage nuances, or interaction effects, failing to compensate for the lack of schema documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as providing 'Top trade setups from the decision engine' and highlights a unique feature: defensive-alternates baked in. It explains the conditional `regime_warranted_alternative` block, which distinguishes it from generic list tools. However, it lacks an explicit verb like 'get' or 'fetch', and does not directly contrast with sibling tools such as `tengu_copilot_top_picks`.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when the alternative block appears (>=70% same direction across 3+ picks) and gives an example of when the brain should consume it, implying the tool is used for trade setups that may need risk-frame fallbacks. It does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

C2.9/5.0
Disambiguation2/5

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.

Naming Consistency2/5

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.

Tool Count1/5

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.

Completeness4/5

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.