One EQUITY cross-horizon ensemble row for a ticker. Despite the legacy mtf path name, the warehouse does NOT emit independent per-timeframe rows, so this tool cannot confirm 1m/4h/1w agreement and must not be cited as multi-timeframe evidence. Crypto requests fail closed.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | Path parameter 'ticker' (required). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It candidly reveals a major limitation (no per-timeframe rows despite the mtf name) and a failure mode (crypto requests fail closed). This goes well beyond a simple 'returns signals' statement, providing critical honesty about what the tool can and cannot do.
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, each earning their place. The first sentence states the core purpose, and the second provides essential caveats about the legacy name and crypto failure. No fluff 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?
For a simple one-parameter tool with no output schema, the description covers the key aspects: what it returns, a critical limitation, and a failure mode. It does not detail the output structure or define 'ensemble row,' but given the low complexity and lack of output schema, this is sufficient context for an agent to use it correctly.
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 schema already describes the only parameter (ticker) with 100% coverage. The description adds meaningful semantics by specifying that the tool is for EQUITY tickers and that crypto requests fail closed, which is crucial for parameter selection. This adds value beyond the bare schema description.
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 resource as "One EQUITY cross-horizon ensemble row for a ticker," which specifies what the tool returns. It distinguishes from the misleading legacy name by stating the warehouse does not emit independent per-timeframe rows. However, it lacks an explicit verb like 'get' or 'retrieve,' making the intent slightly implicit.
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 gives strong negative guidance: it explicitly says the tool cannot confirm 1m/4h/1w agreement and must not be cited as multi-timeframe evidence. It also states crypto requests fail closed, advising against use for crypto. It does not name a specific alternative tool, but the exclusions effectively guide when not to use this tool.
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.
