Live cross-ticker Form-4 insider-transaction feed (alternative-data, last ~20k rows): name, transaction_code, shares, price_per_share, value_usd, shares_owned_following. Call this when the user asks 'are insiders buying or selling?' — one name or market-wide. Optional ticker filter is applied client-side.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| ticker | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It usefully discloses the data window (~20k rows), the returned fields, and the client-side ticker filter behavior. However, it does not explicitly state read-only semantics, pagination/limit behavior, or any error/availability caveats, leaving gaps for a data feed with no annotation safety signals.
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 compact and front-loaded, starting with the core offering, then listing useful fields, and closing with a clear usage trigger. It avoids unnecessary fluff, though the field enumeration adds some length.
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 two optional parameters and no output schema, the description covers the main purpose, basic fields, and the ticker behavior, which is enough for simple selection. It omits details about the limit parameter, sort order, or output shape, and the client-side filtering note hints at potential performance considerations that are not fully explained.
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 adds meaning for the ticker parameter by noting it is optional and applied client-side, but it says nothing about the limit parameter (default 50, max 500), leaving its semantics to the schema alone.
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 a live cross-ticker Form-4 insider-transaction feed and lists the key fields, making the resource and purpose explicit. It does not explicitly compare against sibling insider tools like tengu_v3_intel_insider_trades or tengu_v3_intel_insider_flow, so it falls short of full differentiation.
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?
Provides a concrete trigger: 'Call this when the user asks 'are insiders buying or selling?' — one name or market-wide.' This gives clear context for when to use the tool, but it does not mention when not to use it or name any alternative tools for similar insider data requests.
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.
