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tengu-firm

by io.github.Hlobo-dev

tengu_copilot_score_ticker

Full per-ticker quant analysis. CALL THIS when the user asks about any specific stock (e.g. 'should I buy NVDA', 'what do you think of TSLA'). Returns blended_score, decile, conformal expected-return interval (90% band), 12-voter breakdown, factor tier, regime context, suggested position size, and a self-contained narrative. Use the narrative as a quotable summary; use the structured fields for follow-up questions. NAMESPACE: FIRM's universe is US EQUITIES. Nine tickers (BTC ETH LINK LTC COMP ARB NEAR APT ATOM) are ALSO crypto symbols; for those the response carries a ticker_collision block stating the score describes the US-listed EQUITY. If the user means the CRYPTO asset pass asset_class=crypto, which 404s (no FIRM crypto model yet). For ONE crypto sitting (liquid-book SCAN + scored-ordering RANK + top-N SLEEVE) call GET /api/crypto/sitting — that is DATA, signal_quality_mode=ordering_only, not a forecast. The full liquid book stays on GET /api/crypto/universe (not Alpaca's 36). For overnight movers / watchlist DATA call GET /api/crypto/overnight (X-API-Key) — a SLICE of that universe, data/context, not a score. For ONE US-equity sitting (full-book SCAN + attached factor RANK + top-N SLEEVE) call GET /api/equity/sitting — that is DATA, not a score, and do_not_place_from_mover_rank stays true. NEVER present an equity score as a crypto view.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesPath parameter 'ticker' (required).
asset_classNoequity

TDQS

A4.9/5.0
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 the returned fields, the narrative vs structured data split, the crypto ticker collision behavior, the 404 case for asset_class=crypto, and distinctions between data-only and scored endpoints. This is exceptionally transparent.

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

Conciseness4/5

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

The description is long and dense, but it is front-loaded with the core purpose and each sentence earns its place by preventing specific misuse or clarifying output semantics. It could arguably be tightened, but the structure helps navigate complex edge cases.

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?

With no output schema and no annotations, the description must be self-sufficient. It enumerates the return fields (blended_score, decile, interval, breakdown, factor tier, regime, position size, narrative), addresses ticker collisions, and clearly delineates when this tool is not the right choice. This is complete for a tool of this complexity.

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

Parameters5/5

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

Schema coverage is only 50%, but the description compensates thoroughly by explaining the asset_class enum behavior, including that crypto 404s, and documenting the ticker collision block. It also gives real ticker examples (NVDA, TSLA, BTC) that clarify parameter usage beyond the schema.

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 opens with a specific verb and resource ('Full per-ticker quant analysis') and immediately distinguishes itself from siblings by stating when to call it for specific stock questions. It clearly lists the output fields, making the tool's purpose unmistakable even among many similar ticker tools.

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 explicitly says 'CALL THIS when the user asks about any specific stock' with concrete examples. It also gives clear alternative guidance for crypto assets, overnight movers, and equity sittings, plus a strong 'NEVER' directive to prevent misuse.

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.

Resources