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kukapay

Bridge Metrics MCP

get_transactions

Retrieve and analyze bridge transactions within a specified date range, filtered by source chain or address, to monitor cross-chain activity.

Instructions

Fetch and return all transactions for a bridge within a specified date range in a table format.
Parameters:
- bridge_id: integer (required) - The ID of the bridge (obtain from list_bridges).
- start_timestamp: integer (optional) - Start Unix timestamp for the date range.
- end_timestamp: integer (optional) - End Unix timestamp for the date range.
- source_chain: string (optional) - Filter transactions bridging from this source chain.
- address: string (optional) - Filter transactions where this address is 'from' or 'to' (format: {chain}:{address}).
- limit: integer (optional) - Limit number of transactions returned (max 6000).
Returns a table of transaction data with key metrics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bridge_idYes
start_timestampNo
end_timestampNo
source_chainNo
addressNo
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so description carries full burden. It mentions 'Fetch and return' assuming read-only, and specifies max limit of 6000. However, it does not disclose potential side effects, rate limits, authentication needs, or pagination behavior. Output description is vague ('key metrics').

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?

Description is well-structured with a clear purpose sentence followed by bullet points for parameters. Each sentence adds value and is not redundant. It is appropriately front-loaded but could be slightly more concise by removing the 'Returns a table' line as output schema exists.

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?

For a tool with 6 parameters and no annotations, the description covers inputs adequately but leaves output vague ('key metrics'). Output schema exists, so return values are not required per rules, but operational details like pagination or error cases are missing. Completeness is average given context.

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 0%, but the description provides detailed explanations for each parameter, including types, requirements, and formats (e.g., address format {chain}:{address}, limit max 6000). This adds significant value beyond the raw schema, though some clarity on default behavior for optional params could be improved.

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?

Description clearly states 'Fetch and return all transactions' with a specific resource (bridge) and scope (date range, table format). It explicitly distinguishes from siblings like get_day_stats and get_historical_volumes which are aggregated metrics, while this is raw transactions.

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 does not explicitly state when to use this tool vs alternatives. It implies usage for fetching transaction data with filters, but lacks guidance on when not to use it (e.g., for summary statistics). The pointer to obtain bridge_id from list_bridges is helpful but not sufficient.

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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