AD token-monitor
OpenClaw Token 实时监控面板。支持：(1) SQLite 持久化存储历史数据 (2) 实时监控当前 Token 消耗（增量曲线） (3) 历史视图查看任意一天的消耗 (4) 按日/时会话汇总 (5) 人民币费用估算（MiniMax 官方定价） (6) 滚轮缩放 X 轴 (7) 图表采样防卡顿。触发场景：(1) 用户要求查看 Token 消耗 (2) 监控 AI 模型使用量 (3) 分析日/小时级别消耗趋势 (4) 排查 Token 异常消耗。
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "email"
Process rating: all ten parameters 49/100
- 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
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (token-monitor) differs from the folder (openclaw-token-monitor)
- 100Tools and files. No external tools needed
- 100Steps. 9 steps
- 100Execution cost. Instruction body is 313 tokens
- 100Running it twice. No mutating operations
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 230: enough signal without eating the budget
- +4Structure: 6 headings
- +3Step-by-step instructions: 9 items
- +4Has examples (2 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.
External checks
ClawHub: suspicious
This appears to be a real token-monitoring dashboard, but it exposes sensitive usage history and control endpoints through an unauthenticated network service.
LLM: suspicious (high) · VirusTotal: · 29 May 2026