SKILLEMALL.ai

BC etherscan-transaction-debugger

Analyze 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 implementation executed, which call reverted, or why two transactions behaved differently. Reconstruct the supported execution path, decode calls and events, summarize asset and permission changes, showcase the relevant Etherscan transaction, contract, token, label, log, and internal-transaction views, and provide plain-English, developer, support, or security-focused explanations with confidence and limitations. Do not use for broad wallet investigations, multi-hop laundering traces, or full contract audits.

ClawHub Agent Skills author: etherscan v1.0.0 MIT-0 11 files · 2 scripts body ≈ 2 531 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

Analyze and explain one or two EVM transactions using live Etherscan data and human-verifiable Etherscan evidence links.

As a process C 51/100 · Has gaps — References files that are not bundled: ../etherscan-flow/SKILL.md

AnalyzerSoftware developmentData and analyticsMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
C
51/100
Has gaps
References files that are not bundled: ../etherscan-flow/SKILL.md
Tools and files w 18
0
Result and completion w 14
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: ../etherscan-flow/SKILL.md

Process rating: all ten parameters 51/100

Will not run. References files that are not bundled: ../etherscan-flow/SKILL.md
  • 0Tools and files. 1 referenced file(s) missing: ../etherscan-flow/SKILL.md
  • 0Result and completion. Does not say what the result is
  • 30Running it twice. 8 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 49 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2531 tokens
  • 100Progress reporting. Reports progress

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +3Description length 813: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 49 items
  • +4Reference files are cited in the instructions (5 of 5)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

External checks

ClawHub: clean
This skill is a coherent Etherscan transaction-analysis helper, and I found no hidden exfiltration, destructive behavior, or persistence.
LLM: benign (high) · VirusTotal: · 24 Sept 2026