AC usage-stats
OpenClaw 使用统计技能。自动分析会话记录，生成 token 消耗、费用、工具使用等完整报告。 触发场景：用户提到"使用统计"、"token 消耗"、"费用分析"、"使用报告"、"使用情况"、 "usage stats"、"token usage"、"消费记录"、"我用了多少"、"统计"等关键词时使用。 关键词：usage, token, stats, 统计, 费用, cost, 消耗, report
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
ReferenceData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
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")
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
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 100Tools and files. No external tools needed
- 100Steps. 17 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 533 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 3 example trigger phrases
- +3Description length 205: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 17 items
- +4Reference files are cited in the instructions (1 of 2)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.
External checks
ClawHub: clean
This skill locally analyzes OpenClaw session logs to create usage reports, and its sensitive file access is disclosed and aligned with that purpose.
LLM: benign (high) · VirusTotal: · 29 May 2026