Institutional-holder history — a holder × quarter matrix of 13F positions (shares per quarter-end + latest value) from the institutional-holdings 13F archive. Call it to track when funds built or exited a stock across quarters; for only the latest snapshot use /intel/sec13f.
| Name | Required | Description | Default |
|---|---|---|---|
| top | No | ||
| ticker | Yes | Path parameter 'ticker' (required). | |
| quarters | No |
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 does describe the output shape (holder × quarter matrix, shares per quarter-end, latest value) and the source archive. However, it omits details like pagination, ordering, limits (e.g., that the 'top' parameter caps the number of holders), or any error conditions. This is adequate but not rich.
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, well-structured sentence. It front-loads the core concept ('Institutional-holder history'), uses a dash to introduce the matrix definition, and ends with an actionable usage directive. Every phrase earns its place without waste.
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 the lack of annotations, output schema, and minimal parameter descriptions, the description provides a useful high-level overview but falls short of full completeness. It explains the data structure and use case, but not the role of the 'top' and 'quarters' parameters, the exact response format, or potential limitations. It is sufficient for a basic understanding but not for advanced 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 description coverage is only 33% (ticker has a boilerplate description; top and quarters have none). The description adds no parameter-specific meaning—it mentions quarters generally but does not explain how 'top' or 'quarters' control the output. This is a clear gap for a 3-parameter tool, and the description fails to compensate for the schema's lack of detail.
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's function: 'Institutional-holder history — a holder × quarter matrix of 13F positions' and explicitly contrasts it with the sibling tool: 'for only the latest snapshot use /intel/sec13f.' The verb 'Call it to track when funds built or exited a stock' provides a specific use case, distinguishing it from related 13F 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 gives direct guidance: 'Call it to track when funds built or exited a stock across quarters' and specifies when NOT to use it: 'for only the latest snapshot use /intel/sec13f.' This explicitly names an alternative tool for a different scenario, meeting the highest bar for this dimension.
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.
