OpenClaw Model Usage

Inspect local OpenClaw model usage directly from session logs. Use when asked for the current model, recent model usage, usage breakdown by model, token tota...

This skill appears to do what it says: parse local OpenClaw session JSONL files and build local summaries and an HTML dashboard. Before installing/running: (1) confirm you have Python 3.12+ available (the package requires it), (2) be aware it will read files under ~/.openclaw/agents by default (so don't run it if those logs are sensitive or you don't want local analysis), (3) the dashboard is written locally (--out path) and is self-contained (no external scripts), and (4) no credentials or network calls are requested by the code—if you need extra assurance, inspect the bundled scripts (scripts/model_usage.py and src/openclaw_model_usage/cli.py) or run the tool in a sandboxed environment. The smoke tests exercise subprocesses for local invocation but those are test-only and not network-related.

Type: OpenClaw Skill Name: openclaw-model-usage Version: 1.2.1 The openclaw-model-usage skill is a legitimate utility designed to analyze local OpenClaw session logs (~/.openclaw/agents) to provide usage summaries and cost reports. The core logic in src/openclaw_model_usage/cli.py reads local JSONL files, aggregates token counts and costs, and generates human-readable summaries or a self-contained HTML dashboard. The code is well-structured, includes comprehensive tests (tests/smoke_test.py), and lacks any indicators of malicious intent such as data exfiltration, unauthorized network access, or obfuscation. The instructions in SKILL.md are aligned with the tool's purpose and provide helpful guidance to the AI agent on distinguishing between real and test data.