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tengu-firm

by io.github.Hlobo-dev

tengu_v3_crypto_events_headlines

Call this for what is BREAKING on crypto-native social and blogs right now, already mapped to coins. Sourced from the accounts that break events — exchange officials, security firms, tier-1 desks — with the post's own timestamp, so it runs minutes to hours ahead of any article. Every item is classified (exploit / halt / depeg / regulatory / listing / delisting / etf / unlock / liquidation) and tagged tier 1 or 2 by whether the account is a known breaking source; tier1_only=true keeps just those. Retweets and replies are dropped — an event is the original post, not the 400 accounts quoting it. The classification is an event TYPE, never a direction: read the price for that. DATA context, not a score. Auth: X-API-Key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
symbolsNo
event_typeNo
tier1_onlyNo
asset_classNocrypto

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and succeeds: it discloses the source accounts, that retweets/replies are dropped, that tier1_only controls source confidence, that classification is event type not direction, that this is 'DATA context, not a score,' and even the required auth method.

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 dense but not bloated. Every sentence adds useful selection or invocation detail, and the key use case is front-loaded in the first sentence. It earns its length.

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?

For a tool with no annotations and no output schema, the description covers sources, filters, classification meaning, caveats, and auth—enough for an agent to select and invoke it correctly. It does not describe return shape or ordering, which keeps it from being fully complete.

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

Parameters3/5

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 adds real meaning for event_type (lists the categories), tier1_only ('keeps just those'), and implies that 'symbols' addresses coins. However, it does not explain limits or asset_class semantics, so compensation is only partial.

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 the exact job: 'what is BREAKING on crypto-native social and blogs right now, already mapped to coins.' It names specific sources, timeliness versus articles, and classification behavior, giving the tool a distinct identity among the many sibling news/crypto tools.

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 explicitly says 'Call this for what is BREAKING' and explains why it is faster than articles, giving clear context for when to use it. It does not name alternatives or explicitly state when not to use this tool, so it stops short of a full 5.

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