Skill: vedantsingh60/token-watch (version 1.2.3)

# TokenWatch **Track, analyze, and optimize token usage and costs across AI providers. Set budgets, get alerts, compare models, and reduce your spend.** Free and open-source (MIT License) • Zero dependencies • Works locally • No API keys required --- ## Why This Skill? After OpenAI's acquisition of OpenClaw, token costs are the #1 concern for power users. This skill gives you full visibility into what you're spending, where it's going, and exactly how to reduce it. ### Problems it solves: - You don't know how much you're spending until the bill arrives - No way to compare costs across providers before choosing a model - No alerts when you're approaching your budget - No actionable suggestions for reducing spend --- ## Features ### 1. Record Usage & Auto-Calculate Costs ```python from tokenwatch import TokenWatch monitor = TokenWatch() monitor.record_usage( model="claude-haiku-4-5-20251001", input_tokens=1200, output_tokens=400, task_label="summarize article" ) # ✅ Recorded: $0.00192 ``` ### 2. Auto-Record from API Responses ```python from tokenwatch import record_from_anthropic_response, record_from_openai_response # Anthropic response = client.messages.create(model="claude-haiku-4-5-20251001", ...) record_from_anthropic_response(monitor, response, task_label="my task") # OpenAI response = client.chat.completions.create(model="gpt-4o-mini", ...) record_from_openai_response(monitor, response, task_label="my task") ``` ### 3. Set Budgets with Alerts ```python monitor.set_budget( daily_usd=1.00, weekly_usd=5.00, monthly_usd=15.00, per_call_usd=0.10, alert_at_percent=80.0 # Alert at 80% of budget ) # ✅ Budget set: daily=$1.0, weekly=$5.0, monthly=$15.0 # 🚨 BUDGET ALERT fires automatically when threshold is crossed ``` ### 4. Dashboard ```python print(monitor.format_dashboard()) ``` ``` 💰 SPENDING SUMMARY Today: $0.0042 (4 calls, 13,600 tokens) Week: $0.0231 (18 calls, 67,200 tokens) Month: $0.1847 (92 calls, 438,000 tokens) 📋 BUDGET STATUS Daily: [████░░░░░░░░░░░░░░░░] 42% $0.0042 / $1.00 ✅ Monthly: [███████░░░░░░░░░░░░░] 37% $0.1847 / $0.50 ⚠️ 💡 OPTIMIZATION TIPS 🔴 Swap Opus → Sonnet for non-reasoning tasks (save ~$8.20/mo) 🟡 High avg cost/call on gpt-4o — reduce prompt length ``` ### 5. Compare Models Before Calling ```python # For 2000 input + 500 output tokens: for m in monitor.compare_models(2000, 500)[:6]: print(f"{m['model']:<42} ${m['cost_usd']:.6f}") ``` ``` gemini-2.5-flash $0.000300 gpt-4o-mini $0.000600 mistral-small-2501 $0.000350 claude-haiku-4-5-20251001 $0.003600 mistral-large-2501 $0.007000 gemini-2.5-pro $0.007500 ``` ### 6. Estimate Before You Call ```python estimate = monitor.estimate_cost("claude-sonnet-4-5-20250929", input_tokens=5000, output_tokens=1000) print(f"Estimated cost: ${estimate['estimated_cost_usd']:.6f}") ``` ### 7. Optimization Suggestions ```python suggestions = monitor.get_optimization_suggestions() for s in suggestions: savings = s.get("estimated_monthly_savings_usd", 0) print(f"[{s['priority'].upper()}] {s['message']}") if savings: print(f" → Save ~${savings:.2f}/month") ``` ### 8. Export Reports ```python monitor.export_report("monthly_report.json", period="month") ``` --- ## Supported Models (Feb 2026) **41 models across 10 providers** — updated Feb 16, 2026. | Provider | Model | Input/1M | Output/1M | |----------|-------|----------|-----------| | Anthropic | claude-opus-4-6 | $5.00 | $25.00 | | Anthropic | claude-opus-4-5 | $5.00 | $25.00 | | Anthropic | claude-sonnet-4-5-20250929 | $3.00 | $15.00 | | Anthropic | claude-haiku-4-5-20251001 | $1.00 | $5.00 | | OpenAI | gpt-5.2-pro | $21.00 | $168.00 | | OpenAI | gpt-5.2 | $1.75 | $14.00 | | OpenAI | gpt-5 | $1.25 | $10.00 | | OpenAI | gpt-4.1 | $2.00 | $8.00 | | OpenAI | gpt-4.1-mini | $0.40 | $1.60 | | OpenAI | gpt-4.1-nano | $0.10 | $0.40 | | OpenAI | o3 | $10.00 | $40.00 | | OpenAI | o4-mini | $1.10 | $4.40 | | Google | gemini-3-pro | $2.00 | $12.00 | | Google | gemini-3-flash | $0.50 | $3.00 | | Google | gemini-2.5-pro | $1.25 | $10.00 | | Google | gemini-2.5-flash | $0.30 | $2.50 | | Google | gemini-2.5-flash-lite | $0.10 | $0.40 | | Google | gemini-2.0-flash | $0.10 | $0.40 | | Mistral | mistral-large-2411 | $2.00 | $6.00 | | Mistral | mistral-medium-3 | $0.40 | $2.00 | | Mistral | mistral-small | $0.10 | $0.30 | | Mistral | mistral-nemo | $0.02 | $0.10 | | Mistral | devstral-2 | $0.40 | $2.00 | | xAI | grok-4 | $3.00 | $15.00 | | xAI | grok-3 | $3.00 | $15.00 | | xAI | grok-4.1-fast | $0.20 | $0.50 | | Kimi | kimi-k2.5 | $0.60 | $3.00 | | Kimi | kimi-k2 | $0.60 | $2.50 | | Kimi | kimi-k2-turbo | $1.15 | $8.00 | | Qwen | qwen3.5-plus | $0.11 | $0.44 | | Qwen | qwen3-max | $0.40 | $1.60 | | Qwen | qwen3-vl-32b | $0.91 | $3.64 | | DeepSeek | deepseek-v3.2 | $0.14 | $0.28 | | DeepSeek | deepseek-r1 | $0.55 | $2.19 | | DeepSeek | deepseek-v3 | $0.27 | $1.10 | | Meta | llama-4-maverick | $0.27 | $0.85 | | Meta | llama-4-scout | $0.18 | $0.59 | | Meta | llama-3.3-70b | $0.23 | $0.40 | | MiniMax | minimax-m2.5 | $0.30 | $1.20 | | MiniMax | minimax-m1 | $0.43 | $1.93 | | MiniMax | minimax-text-01 | $0.20 | $1.10 | > To add a custom model: add it to `PROVIDER_PRICING` dict at the top of `tokenwatch.py`. --- ## API Reference ### `TokenWatch(storage_path)` Initialize monitor. Data stored in `.tokenwatch/` by default. ### `record_usage(model, input_tokens, output_tokens, task_label, session_id)` Record a single API call. Returns `TokenUsageRecord` with calculated cost. ### `set_budget(daily_usd, weekly_usd, monthly_usd, per_call_usd, alert_at_percent)` Configure spending limits. Alerts fire automatically when thresholds are crossed. ### `get_spend(period)` Get aggregated spend. Period: `"today"`, `"week"`, `"month"`, `"all"`, or `"YYYY-MM-DD"`. ### `get_spend_by_model(period)` Spending breakdown by model, sorted by cost descending. ### `get_spend_by_provider(period)` Spending breakdown by provider. ### `compare_models(input_tokens, output_tokens)` Compare costs across all known models. Returns list sorted cheapest first. ### `estimate_cost(model, input_tokens, output_tokens)` Estimate cost before making a call. ### `get_optimization_suggestions()` Analyze usage and return ranked suggestions with estimated monthly savings. ### `format_dashboard()` Human-readable spending dashboard with budget bars and tips. ### `export_report(output_file, period)` Export full report to JSON. ### `record_from_anthropic_response(monitor, response, task_label)` Helper to auto-record from Anthropic SDK response object. ### `record_from_openai_response(monitor, response, task_label)` Helper to auto-record from OpenAI SDK response object. --- ## Privacy & Security - ✅ **Zero telemetry** — No data sent anywhere - ✅ **Local-only storage** — Everything in `.tokenwatch/` on your machine - ✅ **No API keys required** — The monitor itself needs no credentials - ✅ **No authentication** — No accounts or logins needed - ✅ **Full transparency** — MIT licensed, source code included --- ## Changelog ### [1.2.3] - 2026-02-16 - 📋 Updated SKILL.md model table to match code: 41 models across 10 providers ### [1.2.0] - 2026-02-16 - ✨ Added DeepSeek, Meta Llama, MiniMax providers - ✨ Expanded to 41 models across 10 providers - ✨ Updated all Anthropic/OpenAI/Google/Mistral pricing to Feb 2026 rates ### [1.1.0] - 2026-02-16 - ✨ Added xAI Grok, Kimi (Moonshot), Qwen (Alibaba) - ✨ Expanded to 32 models across 7 providers ### [1.0.0] - 2026-02-16 - ✨ Initial release — TokenWatch - ✨ Pricing table for 11 models across 5 providers - ✨ Budget alerts: daily, weekly, monthly, per-call thresholds - ✨ Model cost comparison, cost estimation, optimization suggestions - ✨ Auto-hooks for Anthropic and OpenAI response objects - ✨ Dashboard, JSON export, local-only storage, MIT licensed --- **Last Updated**: February 16, 2026 **Current Version**: 1.2.3 **Status**: Active & Community-Maintained © 2026 UnisAI Community


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)