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get_launch_ta_confluence

[$0.05 per call] News Gurus Intel API — VWAP/Bollinger/RSI/MACD confluence read on a fresh memecoin launch computed over GeckoTerminal OHLCV (public/keyless). Token = mint address or symbol. Optional ?chain= (default solana; solana/base/bsc/ethereum). Returns NG-derived bias/score/factors verdict only — raw candles are not redistributed. Educational data, not financial advice. HOW TO PAY: an x402-capable client settles the payment challenge automatically (USDC on Base, no account needed); wallet-less clients pass a subscriber API key instead (Authorization: Bearer , X-API-Key header, or ?api_key= query) for calls within their plan. Browse every tool + price first with the FREE get_catalog tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNosolana
tokenYes

TDQS

A4.5/5.0
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 does so thoroughly. It discloses the $0.05 per call cost, authentication requirements (x402 or subscriber API key), the data source, the output limitation ('bias/score/factors verdict only — raw candles are not redistributed'), and an educational-data disclaimer.

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 core purpose is front-loaded in the first sentence, but the rest of the description packs pricing, payment mechanics, header options, and catalog referral into a dense single block. This information is useful, but it could be better structured for readability.

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 no output schema and no annotations, the description provides enough context for selection and invocation: what the tool computes, input semantics, chain defaults, cost, authentication, and return scope. It also clarifies that raw candles are not provided, which sets accurate expectations.

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 description coverage is 0%, and the schema only lists token and chain with no explanations. The description significantly enriches both: token is defined as 'mint address or symbol', and chain is described as optional with a default of solana and allowed values enumerated (solana/base/bsc/ethereum).

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 identifies the tool as a 'VWAP/Bollinger/RSI/MACD confluence read on a fresh memecoin launch' using GeckoTerminal OHLCV data. It specifies the exact indicators and asset type, distinguishing it from sibling tools like get_memecoin_movers or get_signals.

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

Usage Guidelines3/5

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

The description gives useful context—such as token input, chain options, and a pointer to browse with get_catalog—but does not explicitly state when to prefer this tool over alternatives or when not to use it. Usage is implied rather than directly contrasted with siblings.

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

B3.4/5.0
Disambiguation5/5

Every tool targets a unique resource or data feed, from agent status and macro snapshots to Polymarket whale analytics and MLB props. There is no overlap or ambiguity between tools, even those within the same domain (e.g., the multiple Polymarket tools are clearly distinguished by their focus on landscape, stats, new wallets, leaders, and flagged whales).

Naming Consistency5/5

The naming follows a consistent get_<resource> pattern for all 35 data retrieval tools, with only verify_memecoin deviating but still using a clear verb-noun structure. The pattern is uniform and predictable, making it easy for an agent to infer the purpose of any tool.

Tool Count2/5

With 36 tools, this significantly exceeds the typical well-scoped range of 3-15. While the server covers a broad range of market intelligence domains, the sheer number of tools makes navigation and selection challenging for an agent, placing it in the 'too many' category.

Completeness4/5

The API provides comprehensive coverage across signals, sentiment, on-chain data, institutional activity, sports, and macro, with both broad aggregate tools and per-symbol/asset specifics. Minor gaps exist, such as a lack of direct news headlines or a fear-greed index, but these are not critical dead ends given the stated purpose of delivering derived intelligence.

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