AC token-cost-guard
Monitor agent token usage and model cost from the active ecosystem's own records, compare the current run with the previous snapshot, and send an alert report when cost growth exceeds a threshold. In OpenClaw it reads OpenClaw session logs; in Hermes agent it reads Hermes logs/state.db instead of OpenClaw. Use when users ask to track token spend, calculate realtime token cost, detect spending spikes, monitor DeepSeek/Kimi/GPT model usage, or set up cost alerts for OpenClaw or Hermes agents.
Monitor agent token usage and model cost from the active ecosystem's own records, compare the current run with the previous snapshot, and send an alert report…
As a process C 54/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches
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: 7. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 54/100
- 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. 1 mutating operations with no state check
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 100Steps. 30 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1402 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)
- +1No license
- +2Single-language instructions
- +3Description length 495: enough signal without eating the budget
- +4Structure: 6 headings
- +3Step-by-step instructions: 30 items
- +3Output format is stated explicitly
- +4Has examples (10 code blocks)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.