ChainRay

Token Sentiment

token.sentiment

Read-onlyIdempotent

On-chain sentiment oracle for any token/chain. Derives market sentiment from 5 on-chain signals: gas trend, gas level, momentum, chain health, ecosystem trend. No LLM. ($0.012)

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "token.sentiment"
  }
}

Input Schema

Name	Required	Description	Default
`chain`	No	EVM chain only. Supported chains: base, ethereum, arbitrum, optimism, polygon, bsc, avalanche, zksync, linea, scroll, blast, mantle, gnosis, polygon-zkevm, mode, sei, celo, manta, taiko, fantom, cronos, opbnb, zora, worldchain, metis, fraxtal, kava, zetachain, filecoin, core-dao, aurora, moonbeam, klaytn, bob, canto, monad, tempo, megaeth, arc, plasma, katana, robinhood, pharos, hyperevm.	base
`token`	No	Token symbol or 'native' for the chain gas asset	native

Output Schema

Name	Required	Description
`note`	No
`chain`	No	Blockchain queried
`score`	Yes	Sentiment score -1 to 1
`token`	Yes
`status`	No
`sources`	No
`available`	No
`sentiment`	Yes	Sentiment direction (bullish/bearish/neutral/unavailable)

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 2, 2026

TDQS

A3.7/5.0

Behavior3/5

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

Annotations already declare readOnly, idempotent, openWorld, non-destructive, so the safety and side-effect profile is fully covered. The description adds the meaningful detail that it's a deterministic signal-based oracle with 'No LLM', which sets expectations about output. It doesn't mention caching, rate limits, or what the sentiment output looks like (though an output schema exists).

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?

Three compact sentences, front-loaded with the resource and scope, then the signal list, then the pricing note. Nothing wasteful, though the '($0.012)' cost tag is stuck at the end and could be folded in.

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?

With annotations, full schema coverage, and an output schema, the description only needs to convey purpose and method, which it does. It's complete enough to invoke correctly, missing only sibling differentiation and any hint of output shape.

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 coverage is 100% and both parameters carry descriptions (chain enum list plus 'native'), so the schema does the heavy lifting. The description adds only 'any token/chain' framing, not new format or semantics. Baseline 3 is appropriate.

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?

States a specific noun phrase (on-chain sentiment oracle) and lists the exact 5 input signals it derives sentiment from. This distinguishes it from siblings like predict.token_momentum and token.trending by scoping it to on-chain gas/health/ecosystem signals rather than price or trade data.

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 implies usage ('for any token/chain', gas/health signals) but names no alternative and gives no when/when-not guidance. Siblings such as predict.token_momentum and token.trending overlap enough that a routing sentence would help.

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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