Refactor remaining skills with resources pattern and allowed-tools
- k8s-quick-status: Add scripts/quick-status.sh, allowed-tools - sysadmin-health: Add scripts/health-check.sh, allowed-tools - usage: Add scripts/usage_report.py, simplify SKILL.md - programmer-add-project: Add allowed-tools All skills now: - Have executable scripts for main operations - Use allowed-tools to restrict capabilities - Have improved descriptions with trigger phrases - Follow the "Skill with Bundled Resources" pattern 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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OpenCode Test
@@ -1,6 +1,6 @@
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---
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name: usage
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description: Track and report model usage across sessions
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description: Track and report model usage across sessions. Use when asked about usage, stats, or session history.
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allowed-tools:
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- Bash
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- Read
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@@ -10,13 +10,13 @@ allowed-tools:
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Query session history and report usage statistics.
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## Data Sources
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## Quick Command
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| Source | Status | Data Available |
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|--------|--------|----------------|
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| `history/index.json` | Available | Session IDs, start times |
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| `history/*.jsonl` | Future | Session content, commands, tokens |
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| `usage/config.json` | Available | Log level, preferences |
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```bash
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python3 ~/.claude/skills/usage/scripts/usage_report.py [range]
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```
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Ranges: `today`, `week` (default), `month`, `all`
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## Command Routing
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@@ -27,11 +27,29 @@ Query session history and report usage statistics.
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| `/usage week` | Last 7 days |
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| `/usage month` | Last 30 days |
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| `/usage all` | All time stats |
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| `/usage --by agent` | Group by agent |
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| `/usage --by skill` | Group by skill |
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| `/usage --by model` | Group by model tier |
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| `/usage --set-level <level>` | Set log level |
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| `/usage --show-config` | Show current config |
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## Data Sources
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| Source | Status | Data |
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|--------|--------|------|
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| `history/index.json` | Available | Session IDs, start times |
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| `usage/config.json` | Available | Log level, preferences |
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## Output Format
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```
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📊 Usage Summary — Week
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Sessions: 12
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Total time: 8h 32m
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Days active: 5
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Model: opus (primary)
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📅 Sessions by Date:
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2026-01-01: 3 sessions (95m)
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2025-12-31: 4 sessions (120m)
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...
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```
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## Log Levels
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@@ -41,111 +59,6 @@ Query session history and report usage statistics.
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| `standard` | + agents, skills, tokens (default) |
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| `detailed` | + commands, delegations, errors |
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## Implementation
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### Query Sessions
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```python
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import json
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from datetime import datetime, timedelta
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from pathlib import Path
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from zoneinfo import ZoneInfo
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LOCAL_TZ = ZoneInfo('America/Los_Angeles')
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HISTORY_DIR = Path.home() / ".claude/state/personal-assistant/history"
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CONFIG_PATH = Path.home() / ".claude/state/usage/config.json"
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def load_sessions():
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index_path = HISTORY_DIR / "index.json"
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if not index_path.exists():
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return []
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with open(index_path) as f:
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data = json.load(f)
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return data.get("sessions", [])
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def filter_sessions(sessions, range_type="week"):
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now = datetime.now(LOCAL_TZ)
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if range_type == "today":
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cutoff = now.replace(hour=0, minute=0, second=0, microsecond=0)
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elif range_type == "week":
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cutoff = now - timedelta(days=7)
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elif range_type == "month":
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cutoff = now - timedelta(days=30)
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else: # all
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return sessions
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filtered = []
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for s in sessions:
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started = datetime.fromisoformat(s["started"])
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if started >= cutoff:
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filtered.append(s)
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return filtered
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def estimate_duration(sessions):
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"""Estimate session duration from consecutive start times."""
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if not sessions:
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return []
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sorted_sessions = sorted(sessions, key=lambda s: s["started"])
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for i, session in enumerate(sorted_sessions):
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if i + 1 < len(sorted_sessions):
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start = datetime.fromisoformat(session["started"])
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next_start = datetime.fromisoformat(sorted_sessions[i + 1]["started"])
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duration = (next_start - start).total_seconds() / 60
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# Cap at 2 hours (likely session gap)
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session["duration_mins"] = min(duration, 120)
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else:
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# Current/last session: estimate 30 mins
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session["duration_mins"] = 30
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return sorted_sessions
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```
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### Generate Report
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```python
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def generate_report(sessions, range_type="week"):
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total_mins = sum(s.get("duration_mins", 0) for s in sessions)
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hours = int(total_mins // 60)
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mins = int(total_mins % 60)
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report = f"""
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📊 Usage Summary — {range_type.title()}
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Sessions: {len(sessions)}
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Total time: {hours}h {mins}m
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Model: opus (primary)
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"""
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return report
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```
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## Output Format
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```
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📊 Usage Summary — Last 7 Days
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Sessions: 12
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Total time: 8h 32m
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Model: opus (primary)
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┌─────────────┬──────────┬────────┐
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│ Agent │ Sessions │ Time │
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├─────────────┼──────────┼────────┤
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│ PA │ 12 │ 8h 32m │
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└─────────────┴──────────┴────────┘
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Note: Detailed metrics available when session
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content logging is enabled.
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```
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## Future Enhancements
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When `history/*.jsonl` files are available:
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- Parse actual commands used
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- Detect skill invocations
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- Count delegations (sonnet/haiku)
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- Estimate token usage
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- Track errors
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## Policy
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- Read-only operations
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109
skills/usage/scripts/usage_report.py
Executable file
109
skills/usage/scripts/usage_report.py
Executable file
@@ -0,0 +1,109 @@
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#!/usr/bin/env python3
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"""Generate usage statistics from session history."""
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import json
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import sys
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from datetime import datetime, timedelta
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from pathlib import Path
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from zoneinfo import ZoneInfo
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LOCAL_TZ = ZoneInfo('America/Los_Angeles')
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HISTORY_DIR = Path.home() / ".claude/state/personal-assistant/history"
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CONFIG_PATH = Path.home() / ".claude/state/usage/config.json"
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def load_sessions():
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"""Load sessions from history index."""
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index_path = HISTORY_DIR / "index.json"
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if not index_path.exists():
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return []
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with open(index_path) as f:
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data = json.load(f)
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return data.get("sessions", [])
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def filter_sessions(sessions, range_type="week"):
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"""Filter sessions by time range."""
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now = datetime.now(LOCAL_TZ)
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if range_type == "today":
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cutoff = now.replace(hour=0, minute=0, second=0, microsecond=0)
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elif range_type == "week":
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cutoff = now - timedelta(days=7)
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elif range_type == "month":
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cutoff = now - timedelta(days=30)
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else: # all
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return sessions
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filtered = []
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for s in sessions:
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try:
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started = datetime.fromisoformat(s["started"])
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if started.tzinfo is None:
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started = started.replace(tzinfo=LOCAL_TZ)
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if started >= cutoff:
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filtered.append(s)
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except (KeyError, ValueError):
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continue
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return filtered
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def estimate_duration(sessions):
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"""Estimate session duration from consecutive start times."""
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if not sessions:
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return []
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sorted_sessions = sorted(sessions, key=lambda s: s["started"])
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for i, session in enumerate(sorted_sessions):
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if i + 1 < len(sorted_sessions):
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start = datetime.fromisoformat(session["started"])
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next_start = datetime.fromisoformat(sorted_sessions[i + 1]["started"])
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duration = (next_start - start).total_seconds() / 60
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# Cap at 2 hours (likely session gap)
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session["duration_mins"] = min(duration, 120)
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else:
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# Current/last session: estimate 30 mins
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session["duration_mins"] = 30
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return sorted_sessions
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def generate_report(sessions, range_type="week"):
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"""Generate usage report."""
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sessions = estimate_duration(sessions)
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total_mins = sum(s.get("duration_mins", 0) for s in sessions)
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hours = int(total_mins // 60)
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mins = int(total_mins % 60)
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# Group by date
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by_date = {}
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for s in sessions:
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date = s["started"][:10]
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by_date.setdefault(date, []).append(s)
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report = f"""📊 Usage Summary — {range_type.title()}
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Sessions: {len(sessions)}
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Total time: {hours}h {mins}m
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Days active: {len(by_date)}
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Model: opus (primary)
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"""
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if by_date:
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report += "\n📅 Sessions by Date:\n"
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for date in sorted(by_date.keys(), reverse=True)[:7]:
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count = len(by_date[date])
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day_mins = sum(s.get("duration_mins", 0) for s in by_date[date])
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report += f" {date}: {count} sessions ({int(day_mins)}m)\n"
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return report
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def main():
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range_type = sys.argv[1] if len(sys.argv) > 1 else "week"
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sessions = load_sessions()
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filtered = filter_sessions(sessions, range_type)
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report = generate_report(filtered, range_type)
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print(report)
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if __name__ == "__main__":
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main()
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