Quarterly cross-ticker federal-contracts feed (alternative-data) — top-line award totals only, lighter than per-ticker tengu_v3_intel_gov_contracts (no agency or description fields). Call this for 'which companies win government money?' screens; use tengu_v3_intel_gov_contracts for line-items.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| ticker | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It does add useful context: the data is quarterly, cross-ticker, top-line totals only, and lacks agency/description fields. However, it does not clarify key operational traits such as whether the 'ticker' parameter is accepted or ignored, update frequency or 'live' semantics, or any rate limits or return format. The description is partially transparent but leaves important behavioral gaps.
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 exceptionally concise: two sentences deliver the data cadence, scope, granularity, sibling comparison, and usage guidance. Every clause earns its place, with no filler or repetition.
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 simple 2-parameter tool with no output schema, the description provides enough context for high-level tool selection and even names the alternative. However, it omits parameter semantics and precise return-shape details, so an agent would need to infer or guess how to invoke it correctly. This leaves it at the minimum viable level but not complete.
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%, and the description does not directly explain the 'limit' or 'ticker' parameters. The phrase 'cross-ticker' implies the ticker may be optional or not the primary filter, but this is not spelled out. The tool name and standard parameter names provide some implicit meaning, but the description fails to compensate for the missing schema descriptions, leaving ambiguity about how to set parameters.
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 specific verb+resource: a quarterly cross-ticker federal-contracts data feed providing top-line award totals. It explicitly differentiates itself from the sibling tool 'tengu_v3_intel_gov_contracts,' which is described as per-ticker with line-items, making the tool's scope unambiguous.
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 provides explicit usage guidance: 'Call this for "which companies win government money?" screens; use tengu_v3_intel_gov_contracts for line-items.' This directly states when to use this tool versus the alternative, satisfying the highest bar for usage guidelines.
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.
