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tengu_v3_transcripts_list

List a company's earnings calls and investor-event transcripts (licensed institutional, 1.75M calls), newest first — call this FIRST to get the event_id you pass to the full-text route. One row per call (versions collapsed to the best copy: Proofed > Edited > Spellchecked) with date, title and event type. Full text coverage is 2020-2025; older calls are metadata-only.

Input Schema

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

TDQS

A4.3/5.0
Behavior4/5

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 reveals important behavior: newest-first ordering, version collapsing (Proofed > Edited > Spellchecked), and full-text coverage limits. It does not mention pagination behavior or error handling, but it provides substantial context beyond the tool name.

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 is three sentences, each providing distinct and valuable information: purpose and workflow, output row structure, and coverage limitations. It is front-loaded with the core action and avoids redundant phrasing.

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

Completeness4/5

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

Given the tool has no output schema, the description does a good job of explaining what the caller receives: one row per call with date, title, event type, and the event_id for subsequent calls. It also sets expectations about data coverage. However, it doesn't clarify the 'since' parameter format or how pagination works, which are minor gaps for a listing tool.

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

Parameters2/5

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

Schema description coverage is low (33%: only ticker is described). The description does not elaborate on the optional parameters 'limit' or 'since', leaving their semantics to the schema. It only implies the ticker via 'a company's earnings calls,' which is minimal compensation for the low schema coverage.

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 'List a company's earnings calls and investor-event transcripts' with a specific verb and resource. It also distinguishes itself from sibling tools by saying 'call this FIRST to get the event_id you pass to the full-text route,' which identifies its role in the workflow.

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

Usage Guidelines5/5

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

The description gives explicit usage direction: 'call this FIRST' to obtain the event_id for the full-text route. This clearly states when to use the tool and its position relative to the transcript_text tool. It also notes coverage limitations (2020-2025 full text, older metadata-only), which helps decide if this tool is appropriate.

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.