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tengu-firm

by io.github.Hlobo-dev

tengu_crypto_universe

The FULL liquid crypto universe FIRM prices (~419 pairs in one vendor call), ranked by 24h dollar volume. Stables out. Default floor $1M 24h. The cap IS that floor — this does NOT silently return top-50 or Alpaca's 36 USD pairs. The ranked sitting sleeve is GET /api/crypto/sitting; this endpoint is the full liquid book, not a broker-listed toy set. Optional limit/offset paginate the same book (has_more / next_offset); they do not hide names. Honest counts: priced, excluded_stable, below_floor, returned. Overnight (GET /api/crypto/overnight) is a mover SLICE of this book, not a replacement. LIQUIDITY ranking, NOT conviction — expanding coverage is not a signal. FIRM has no validated crypto edge. Auth: X-API-Key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo
asset_classNocrypto
min_dollar_volumeNo

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations, the description fully discloses behavior: excludes stables, applies a default $1M floor, pagination semantics (has_more/next_offset), honest counts, and authentication via X-API-Key. It also warns that FIRM has no validated crypto edge, which is critical for an agent to set expectations.

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 information-dense but every sentence serves a purpose: scope, exclusions, pagination, counts, related endpoints, and caveats. It is longer than typical but efficient, and front-loads the core purpose before diving into nuances.

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 the tool's complexity and the presence of closely related siblings, the description is exceptionally complete. It covers return contents, ranking criteria, exclusions, pagination, counts, related endpoints, and interpretational warnings, all without an output schema. The agent can use this tool correctly and avoid confusion.

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 has zero descriptions, so description must compensate. It explains limit/offset pagination on the same book, the min_dollar_volume floor, and implies asset_class is fixed to crypto. It does not explicitly name parameter keys but conveys semantics clearly enough for an agent to infer usage.

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 explicitly states it returns the FULL liquid crypto universe with FIRM pricing, ranked by 24h dollar volume, scoping to ~419 pairs. It clearly distinguishes from sibling tools by naming the sitting sleeve and overnight endpoints and explicitly stating it is not a top-50 or Alpaca subset.

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?

Provides explicit when-to-use guidance: this is the full liquid book vs the sitting sleeve (GET /api/crypto/sitting) and overnight mover slice (GET /api/crypto/overnight). Also clarifies it is for liquidity ranking, not conviction, and warns against treating coverage expansion as a signal.

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