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tengu_v3_credit_bonds

FINRA TRACE corporate-bond trade prints for one issuer — individual OTC trades (price, yield, volume, buy/sell side) showing where the company's bonds ACTUALLY trade (realised credit spreads, not quotes). Matched by the FINRA bond-symbol prefix of the equity ticker; window spans at most 90 days (422 beyond). TRACE on licensed-research lags realtime by months — when the default recent window is empty the response includes latest_available; page backwards from it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNo
limitNo
startNo
tickerYesPath parameter 'ticker' (required).

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses key behavioral traits: the maximum 90-day window, potential data lag of months, the fallback to 'latest_available' when the default window is empty, and the need to page backwards. This is beyond what the schema provides and is highly actionable.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description packs dense, relevant information into three tightly structured sentences: purpose/content, matching/window, and lag/paging behavior. Every clause adds value; no filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given there is no output schema and no annotations, the description is remarkably complete: source (FINRA TRACE), scope (one issuer), content (price, yield, volume, side), matching logic, time window, data lag, fallback, and pagination guidance. An agent can reasonably invoke this tool and interpret responses without additional external knowledge.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is low (25%), with only 'ticker' described. The description compensates by explaining the matching mechanism (FINRA bond-symbol prefix), the window span (at most 90 days), and the paging behavior ('page backwards from latest_available'). This adds meaningful context for start/end and limit, though it doesn't detail exact date formats.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: it provides FINRA TRACE corporate-bond trade prints for one issuer, with specific data fields (price, yield, volume, buy/sell side). It distinguishes itself from sibling credit tools by emphasizing realized credit spreads on actual OTC trades rather than quotes, and the matching mechanism via FINRA bond-symbol prefix.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use this tool: when you need actual bond trade prints and realized credit spreads for a specific issuer, contrasting with 'not quotes'. It also provides operational guidance on the 90-day window and lag, but it doesn't explicitly name alternative tools or state explicit exclusion criteria, so a slight gap remains.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

C2.9/5.0
Disambiguation2/5

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.

Naming Consistency2/5

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.

Tool Count1/5

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.

Completeness4/5

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.