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covalenthq

GoldRush MCP Server

by covalenthq

log_events_by_topic

Retrieve all event logs matching a specific topic hash across all contracts on a blockchain. Ideal for tracking event types like transfers or approvals across multiple contracts.

Instructions

Commonly used to get all event logs of the same topic hash across all contracts within a particular chain. Useful for cross-sectional analysis of event logs that are emitted on-chain.Requires chainName (blockchain network) and topicHash (the event signature hash). Optional parameters include block range (startingBlock, endingBlock), secondaryTopics for filtering by additional parameters, and pagination settings (pageSize default 10, pageNumber default 0). Returns decoded event logs matching the specified topic hash, ideal for tracking specific event types across multiple contracts on a blockchain.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNameYesThe blockchain network to query (e.g., 'eth-mainnet', 'matic-mainnet', 'bsc-mainnet').
topicHashYesThe event signature hash (topic[0]) to search for. This is the keccak256 hash of the event signature.
startingBlockNoStarting block number to begin search from. Use with endingBlock to define a range.
endingBlockNoEnding block number to search until. Use with startingBlock to define a range.
secondaryTopicsNoAdditional topic filters (topic[1], topic[2], topic[3]) to narrow down the search.
pageSizeNoNumber of log events to return per page. Default is 10, maximum is 100.
pageNumberNoPage number for pagination, starting from 0. Default is 0.
Behavior3/5

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

No annotations are present, so the description bears full burden. It mentions pagination defaults and queries across contracts, but does not disclose rate limits, authentication needs, or behavior on invalid parameters.

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 concise and front-loaded with purpose and usage, then lists parameters. It is efficient with no fluff, though could be more structured with bullet points.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema is provided, and while required and optional parameters are explained, the return format is only briefly mentioned as 'decoded event logs.' Additional details on pagination behavior or block range limits would improve completeness.

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% with solid parameter descriptions. The description adds context (e.g., block range, secondaryTopics) but does not significantly augment the schema details.

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 states the tool retrieves event logs by topic hash across all contracts on a given chain, distinguishing it from similar tools like log_events_by_address which filter by address.

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 indicates it is 'commonly used' for cross-sectional analysis but does not explicitly state when to use alternatives like log_events_by_address or provide exclusions.

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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