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Found 16 Skills
Skill for adding feature gating and usage tracking using Autumn.
Implement usage-based billing with Flowglad including recording usage events, checking balances, and displaying usage information. Use this skill when adding metered billing, tracking API calls, or implementing consumption-based pricing.
Use when integrating MCPCat analytics into a TypeScript MCP server, adding mcpcat to an existing TypeScript MCP project, setting up MCP server usage tracking, or when the user mentions mcpcat, MCPCat, or MCP analytics in a TypeScript context
fal.ai Platform APIs for model management, pricing, usage tracking, and cost estimation. Use when user asks "show pricing", "check usage", "estimate cost", "setup fal", "add API key", or platform management tasks.
Platform APIs for model management, pricing, and usage tracking
Expert in observing, benchmarking, and optimizing AI agents. Specializes in token usage tracking, latency analysis, and quality evaluation metrics. Use when optimizing agent costs, measuring performance, or implementing evals. Triggers include "agent performance", "token usage", "latency optimization", "eval", "agent metrics", "cost optimization", "agent benchmarking".
Implement subscription tier-based feature gating and usage limits. Centralized tier configuration, database usage tracking, and clean APIs for checking limits.
Track LLM API costs in real-time across multiple providers. Monitor token usage, spending limits, budget alerts, and cost attribution per job or task.
Use when billing for AI model token usage — setting up @commet/ai-sdk tracked() middleware, configuring balance consumption model plans with AI model pricing, tracking input/output/cache tokens, cost calculation with margins, or building AI products that need usage-based billing.
Query AI coding agent usage, costs, and token consumption. Supports Claude Code, Codex CLI, OpenClaw, and OpenCode. Ask about spending, token usage, model costs, session history, API call counts. Actions: check usage, show cost, compare models, list sessions, analyze spending, token breakdown. Time ranges: today, this week, this month, this year, last N days, custom dates.
Analyzes Claude Code session transcripts (JSONL files) to reveal context window content, token usage patterns, and decision-making processes using view_session_context.py tool. Use when debugging Claude behavior, investigating token patterns, tracking agent delegation, or analyzing context exhaustion. Triggers on "why did Claude do X", "analyze session", "check session logs", "context window exhaustion", or "track agent delegation".
Show detailed token ROI report across all tracked sessions