Credit-index composites — the credit market's VIX-equivalents: CDX (NA IG/HY) + iTraxx (Europe/Asia/SovX) daily composite spreads and prices by series/version/tenor, 2018 to T-2. Call it for credit-market risk appetite, spread-widening episodes, or cross-asset stress context. FRESHNESS IS T-2 (daily composite) — never present as realtime.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| limit | No | ||
| family | No | ||
| index_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. It discloses a key non-obvious behavior: data is T-2 daily composite and must never be presented as realtime. This is essential to prevent agent errors. It does not cover other behaviors like output format or pagination, but the most critical caveat is explicitly highlighted.
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 dense sentences: what the tool is, when to use it, and a key caveat. The freshness warning is effectively highlighted with capital letters. Every sentence adds value and there is no 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 covers the main purpose and the most important caveat, which is good given the absence of an output schema. However, it leaves parameter usage vague (especially days and limit) and does not specify what the response will look like. For a simple data retrieval tool this is acceptable but not fully 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%, so the description must compensate. It partially explains the family parameter by connecting CDX/iTraxx to geographies, but it does not explain the days, limit, or index_ticker parameters. The phrase 'by series/version/tenor' hints at index_ticker meaning but lacks concrete syntax or defaults. This is insufficient for a 4-parameter tool with no schema descriptions.
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 resource as 'Credit-index composites' and specifies the exact components (CDX NA IG/HY, iTraxx Europe/Asia/SovX), data type (daily composite spreads and prices), and date range (2018 to T-2). This distinguishes it from sibling tools like credit_bonds or credit_cds_history, with a specific verb 'Call it for' and clear scope.
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 use the tool: 'Call it for credit-market risk appetite, spread-widening episodes, or cross-asset stress context.' It also provides a critical usage caution about freshness ('never present as realtime'). However, it does not name alternative tools or explicitly state when not to use it, so it falls just 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.
