ChainRay

Context Brief

util.context_brief

Read-onlyIdempotent

CaaS (Context as a Service): Aggregates real-time on-chain signals into a structured context brief for agent decision-making. Intents: swap (gas+price+whales), bridge (multi-chain gas), invest (yields+trending), monitor (whales+gas), general (all signals). No LLM cost — pure data. Use at the start of a swap, bridge, invest, monitor, or general workflow to collect the relevant signals in one structured brief. Use focused tools when the agent already knows the exact data it needs.

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": "util.context_brief"
  }
}

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
`intent`	No	Agent's intent for the context brief	general

Output Schema

Name	Required	Description
`chain`	Yes	Blockchain queried
`intent`	Yes
`signals`	Yes
`advisory`	Yes
`timestamp`	Yes	Unix timestamp ms
`oracleType`	Yes
`signalCount`	Yes
`signalQuality`	Yes
`recommendations`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 2, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, and openWorld, so the safety profile is covered. The description adds genuinely useful context beyond them: 'No LLM cost — pure data' and a per-intent breakdown of which signals are aggregated (swap = gas+price+whales, etc.). It doesn't describe pagination or freshness/latency characteristics, but the additions are substantive.

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?

Front-loads the purpose and packs intent semantics and the use/avoid guidance densely with little waste. The intent parenthetical list is information-dense but each entry earns its place by clarifying the param.

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 an output schema present and rich annotations, the description needn't explain return values. It covers purpose, intent behavior, and routing, leaving only minor details like data freshness undisclosed — adequate for a 2-param, zero-required aggregator.

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 coverage is 100% and both params are enums, so the schema already lists valid values. The description goes further by explaining what each intent value aggregates (swap=gas+price+whales, bridge=multi-chain gas, invest=yields+trending, monitor=whales+gas), adding meaning the terse schema description ('Agent's intent') lacks.

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 verb (aggregates) and resource (real-time on-chain signals into a structured context brief) and immediately frames it as 'Context as a Service' for agent decision-making. It differentiates itself from the many focused signal siblings by explicitly routing agents to 'focused tools' instead.

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?

Explicitly states when to use it ('Use at the start of a swap, bridge, invest, monitor, or general workflow') and when not to ('Use focused tools when the agent already knows the exact data it needs'). The condition selecting the alternative is spelled out, leaving nothing to inference.

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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