AC gas-fee-tracker
Track live EVM gas fees across Ethereum, Base, Polygon, and Arbitrum using free public RPC endpoints with no API key required. Classifies current gas as low, medium, or high against configurable thresholds, logs snapshots to a JSONL history file over time, and supports threshold alerts for scripting into automations. Useful for crypto trading, defi, smart contract deployment, and passive income bots that need to time on-chain transactions to avoid overpaying for gas. Complements whale-tracking and defi yield-farming workflows by timing execution around cheap gas windows.
Track live EVM gas fees across Ethereum, Base, Polygon, and Arbitrum using free public RPC endpoints with no API key required.
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
edit-residuethe text marks something as outdated (lines 45): check that old rules are not kept next to new ones — the full check reads the text for contradictions
Process rating: all ten parameters 53/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 3 mutating operations with no state check
- 100Tools and files. No external tools needed
- 100Steps. 5 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 347 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 577: enough signal without eating the budget
- +4Structure: 5 headings
- +3Step-by-step instructions: 5 items
- +4Has examples (4 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.