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Etherscan

by io.github.pipeworx-io

List Transactions

list_transactions
Read-onlyIdempotent

List transactions for an address. type controls which list: "normal" (regular EOA txs), "internal" (contract-internal value transfers), "erc20" (ERC-20 transfers), "erc721" (NFT transfers), "erc1155" (multi-token transfers).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number (default 1)
sortNoasc | desc (default desc)
typeNonormal | internal | erc20 | erc721 | erc1155 (default normal)
chainNoChain slug or chain ID (default ethereum)
offsetNoResults per page (default 25, max 10000)
addressYesAddress to inspect
endblockNoEnd block (default latest = 99999999)
startblockNoStart block (default 0)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesTransaction type: normal|internal|erc20|erc721|erc1155
countYesNumber of transactions returned
addressYesThe queried address
chain_idYesNumeric chain ID
chain_nameYesHuman-readable chain name or null
transactionsYesArray of transaction objects from Etherscan API

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already indicate read-only and idempotent behavior. The description adds the behavioral trait that 'type' controls which transaction subset is returned, which is valuable context beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences: first states the main purpose, second explains the key parameter. No wasted words, front-loaded with the essential action.

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?

Given the 8 parameters and existing output schema, the description covers the core listing functionality. It doesn't detail pagination or sorting, but those are standard and documented in the schema.

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%, baseline 3. The description adds semantic value for the 'type' parameter by explaining what each enum value means (e.g., 'internal' for contract-internal transfers), which is not in the schema description.

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 tool name and description clearly state 'list transactions for an address', specifying the action and resource. The 'type' parameter distinguishes five categories, and no sibling tool overlaps directly.

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

Usage Guidelines4/5

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

The description explains when to use each 'type' value, but does not explicitly mention when not to use this tool or point to alternative tools for balances or other queries. However, the context implies its use for transaction history.

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

A3.8/5.0
Disambiguation1/5

Multiple tools serve nearly identical purposes (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research) with only marginal differences, and the Polymarket family (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_fill_risk, polymarket_edge_tracker, polymarket_kalshi_spread) heavily overlaps in its goal of finding betting edges. An agent would struggle to pick the right tool without reading every description in detail.

Naming Consistency3/5

All names use snake_case, but the pattern is inconsistent: verb_noun (get_balance, list_transactions), noun phrases (entity_profile, recent_changes), brand prefixes (pipeworx_trending, polymarket_edges), and adjectival forms (deep_research, compare_entities). The naming is readable but does not follow a single predictable convention.

Tool Count2/5

With 36 tools, the count exceeds the 25+ threshold for 'too many' even for a general-purpose data server. The situation is worsened by the fact that the server is named Etherscan but only 5 of the 36 tools relate to Ethereum/blockchain, making the count unjustified for the apparent purpose.

Completeness4/5

For the de facto domain (Pipeworx data routing, prediction-market research, entity profiles, claim validation, subscriptions, memory), the tool surface is quite comprehensive: it covers lookup, research, comparison, grounding, and monitoring. Missing are a few edge operations (e.g., no Etherscan transaction-by-hash tool), but the broader domain is well-covered with only minor gaps.

Resources