Quarterly corporate lobbying spend for one ticker from the alternative-data feed (limit, default 50). Call this when the user asks how much a company spends lobbying or whether its policy exposure is growing; pair with tengu_v3_intel_gov_contracts for the government-contract side of the same story.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| ticker | Yes | Path parameter 'ticker' (required). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral transparency burden. It discloses the quarterly frequency, one-ticker scope, and default limit, which adds context beyond the raw schema. However, it does not describe the exact response structure, historical depth, or any coverage/rate limitations, leaving key behavioral details unspecified.
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 concise and front-loaded: the first sentence states what the tool returns, and the second gives usage guidance and a sibling pairing. Every sentence serves a purpose 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?
This is a simple two-parameter tool with no output schema, so the description needs to set expectations about the return value. It covers what, when, and a related alternative, but it omits the output form (list vs single value) and any data-coverage caveats. Given the absence of an output schema and annotations, this is a notable gap.
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 50% (ticker has a boilerplate path-parameter note, limit has no description). The description adds some meaning by clarifying that the tool operates on one ticker and mentioning the default limit of 50, but it does not explain parameter syntax, value formats, or additional constraints beyond what the schema already provides.
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 tool as returning quarterly corporate lobbying spend for a single ticker from the alternative-data feed, including the default limit. It also distinguishes itself from the sibling tool tengu_v3_intel_gov_contracts by explicitly pairing them as complementary, which helps differentiate purpose.
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 call the tool: 'when the user asks how much a company spends lobbying or whether its policy exposure is growing.' It also recommends pairing with a sibling tool, giving clear context and an alternative for related but different needs.
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.
