crypto-news: one-shot per-coin intel summary. Parallel-fetches recent news (24h) + 7-day sentiment stats + trending headlines. The single call to make when asked 'what's going on with BTC?' or any crypto-name analysis. 90s cache.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | Path parameter 'ticker' (required). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description discloses meaningful behavioral traits: parallel-fetching, time windows (24h news, 7-day sentiment), and a '90s cache.' This provides useful context beyond the bare function name, though it omits details like rate limits or error behavior, which are not critical for a read-only summary.
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 three compact sentences: purpose, content, and usage guidance, followed by a cache note. It is front-loaded and has no filler words, maximizing information density.
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 single-parameter tool with no output schema or annotations, the description adequately covers what the tool does, when to use it, and caching behavior. It does not describe the output format, but the 'intel summary' framing and the absence of an output schema make this acceptable.
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 only parameter 'ticker' has a schema description that merely says 'Path parameter (required),' offering no semantic meaning. The tool description compensates by referring to 'per-coin' and 'crypto-name analysis' and using 'BTC' as an example, making clear the expected input is a cryptocurrency ticker.
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 opens with 'crypto-news: one-shot per-coin intel summary' and specifies it 'Parallel-fetches recent news (24h) + 7-day sentiment stats + trending headlines.' This clearly defines the tool's function and differentiates it from granular crypto news siblings by positioning it as 'The single call to make when asked...'
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?
It explicitly states the use case: 'The single call to make when asked "what's going on with BTC?" or any crypto-name analysis.' This tells the agent when to use it, though it does not name specific alternative tools or provide explicit when-not-to-use exclusions.
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.
