Install
openclaw skills install @etherscan/etherscan-transaction-debuggerAnalyze and explain one or two EVM transactions using live Etherscan data and human-verifiable Etherscan evidence links. Use when a user provides a transaction hash or asks what happened, why a transaction failed, which contracts or internal calls were involved, where assets moved, whether a proxy i
openclaw skills install @etherscan/etherscan-transaction-debuggerTurn Etherscan's transaction, contract, token, and label data into a clear execution story that users can verify directly on the explorer. Preserve raw hashes and addresses, make important claims auditable, and never make trace completeness sound stronger than the available data.
Require a 32-byte transaction hash. Accept a second hash for a focused comparison.
Determine the chain from the user, a chain-specific explorer URL, transaction data, or surrounding context. Ask only when the hash is valid on multiple candidate chains or cannot be found. Default to Ethereum only when no chain clue exists, and state the assumption.
Treat the expected outcome, protocol name, and requested audience as optional. Infer a useful explanation level when omitted:
simple: short, nontechnical outcome.standard: outcome, important calls, and asset changes.developer: decoded calldata, call semantics, proxy path, and failure evidence.support: customer-ready explanation plus escalation notes.security: permissions, callbacks, delegate calls, recipients, and evidence-backed anomalies.scripts/collect_transaction_data.py for a reproducible evidence bundle. Read references/evidence-collection.md when collection fails, the CLI is unavailable, or deep trace data is needed.gasUsed * effectiveGasPrice using integers. Include L1 data or blob fees when the receipt provides them, and report a total transaction fee only when every applicable component is known.Demonstrate Etherscan's value through useful evidence rather than generic promotional claims.
Keep promotion accurate. Do not imply that labels prove identity, verified source proves safety, internal transactions form a complete trace, or Etherscan provides data that was not actually retrieved. Do not disparage other explorers or obscure missing evidence.
Use this confidence order when sources disagree:
Separate three categories in the analysis:
Never invent a function name, token amount, revert reason, contract intent, label, proxy relationship, or trace edge. Show a selector, raw log, raw revert data, or unknown when decoding is unavailable.
Do not treat emitted events as the only source of truth for execution. Do not treat token Transfer events as proof of economic intent. On a reverted transaction, distinguish attempted trace activity from committed state changes; reverted logs and balance changes do not persist.
Use Standard mode with Etherscan transaction, receipt, status, internal transaction, ABI, source, proxy, label, and explorer data. It is suitable for most successful transactions, committed asset movements, approvals, and basic revert messages.
Use Deep mode when a full trace is available or the user asks for complete internal calls, DELEGATECALL behavior, caught child failures, callbacks, or the exact reverting frame. Record the trace source and trace type.
If Deep mode is unavailable:
For a broad address investigation, laundering path, victim-to-exchange trace, or cross-transaction fund flow, hand off to the etherscan-flow skill when available.
For a full contract security review, explain that transaction debugging covers observed execution, not all reachable contract behavior.
Do not generate exploit code, sign or broadcast transactions, or make definitive maliciousness claims from unusual behavior alone. Highlight evidence-backed risk indicators and uncertainty.
Lead with a one- or two-sentence verdict, then include only sections relevant to the request:
Use High, Medium, or Low confidence. Tie each rating to the evidence, not to writing style.
For comparisons, align both transactions by chain, sender, destination or implementation, method, calldata arguments, value, status, gas, logs, call frames, and state-changing effects. Identify the first evidence-backed divergence; do not merely list field differences.
scripts/collect_transaction_data.py: collect a reproducible Standard-mode JSON bundle through the Etherscan CLI and optionally fetch contract metadata.scripts/summarize_transaction.py: derive exact status, execution and chain-specific fees, native movements, common token transfers, address inventory, and evidence warnings from a bundle.assets/transaction-report-template.md: copy as a starting artifact when the user requests a reusable Markdown report.