Returns-correlation mesh around a seed ticker — nodes = tickers, edges = |rho| >= 0.6, from the 36-month realised-returns sidecar (depth expands the neighborhood). PRIMARY tool for 'what moves with X?' and finding hedge or pair candidates. Caveat: needs 36-month overlap; a freshly-listed or thinly-traded seed may be absent.
| Name | Required | Description | Default |
|---|---|---|---|
| seed | Yes | ||
| depth | No |
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 correlation threshold, time window, depth behavior, and the absence failure mode. This is strong, but it omits details about the exact result format (e.g., whether raw rho values are included, pagination, or limits), preventing a 5.
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 two concise sentences that front-load the core purpose, then add crucial caveats and context. Every phrase earns its place with no redundant filler.
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 tool with no output schema, the description gives a clear mental model of the graph (nodes/edges/threshold/time window) and warns about data limitations. However, it lacks specifics on the return payload structure (e.g., adjacency list, node IDs, whether correlation values are included), which is a notable gap given the absent output schema.
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 description coverage is 0%, so the description must compensate. It explains 'seed' as the central ticker and 'depth' as expanding the neighborhood, but the depth semantics remain vague (e.g., does depth=2 mean two hops?). The schema provides defaults and bounds, but the meaning is only partially enriched.
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 opens with a specific verb+resource: "Returns-correlation mesh around a seed ticker" and clearly defines the output (nodes = tickers, edges = |rho| >= 0.6). It further clarifies the use case as "PRIMARY tool for 'what moves with X?'" which distinguishes it from sibling research tools.
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 explicitly states when to use this tool ("PRIMARY tool for 'what moves with X?' and finding hedge or pair candidates") and includes a caveat about 36-month overlap for freshly-listed or thinly-traded seeds, indicating when it may not work. It does not name alternative tools, so it misses the 'when-not' and 'alternatives' rubric for a 5.
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.
