Federal government contracts awarded to one ticker's company from the alternative-data feed (limit, default 50). Call this when the user asks how much government business a company wins or whether contract awards are accelerating; pair with tengu_v3_intel_lobbying for the lobbying-spend side.
| 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?
With no annotations provided, the description carries the full burden for behavioral disclosure. It mentions the data source ('alternative-data feed') and the default limit, but does not state whether this is a safe read operation, what the response contains, whether results are sorted chronologically, or any pagination or rate-limit behavior. This is a notable gap for a data-retrieval tool.
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 sentences long, front-loaded with the core function, followed by concrete usage guidance. Every clause contributes value, and there is 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?
The description explains the tool's purpose and when to call it, which is adequate for a simple two-parameter retrieval. However, since there is no output schema or annotations, it would benefit from mentioning the response shape (e.g., contract amounts/dates) or how the data supports detecting acceleration. It also leaves ambiguity against the sibling gov_contracts_live tool.
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 documents the required ticker and the limit constraints (default, min, max), but only ticker has a schema description. The description adds the meaning that the ticker refers to 'one ticker's company' and mentions the default limit, but it mostly restates what the schema already provides. With 50% schema coverage, the description offers marginal extra value.
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 returns federal government contracts awarded to a given ticker's company, using a specific verb ('awarded') and resource scope. It also pairs it with tengu_v3_intel_lobbying to distinguish the complementary data, though it does not explicitly differentiate from the similarly named sibling tengu_v3_intel_gov_contracts_live.
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 explicit use cases: 'when the user asks how much government business a company wins or whether contract awards are accelerating.' It also recommends pairing with tengu_v3_intel_lobbying for the lobbying-spend side, which is clear guidance. It lacks 'when not to use' exclusions, so it stops short of 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.
