claude-code-ultimate-guide/guide/observability.md
Florian BRUNIAUX ac50ee7ad8 docs: add monitoring & activity audit sections to observability guide
- guide/observability.md: +3 sections (Activity Monitoring, External Tools, Proxying)
  - Activity Monitoring: JSONL tool_use audit, jq queries, sensitive pattern detection
  - External Tools: ccusage / claude-code-otel / Akto / MLflow / ccboard comparison
  - Proxying: NODE_EXTRA_CA_CERTS, ANTHROPIC_API_URL, mitmproxy, Python proxy
- docs: ccboard Activity module implementation plan (Tab 10, Rust models, SQLite cache)
- docs: Mergify cross-system support evaluation

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-21 20:29:05 +01:00

768 lines
26 KiB
Markdown

---
title: "Session Observability & Monitoring"
description: "Track Claude Code usage, estimate costs, and identify patterns across development sessions"
tags: [observability, guide, performance]
---
# Session Observability & Monitoring
> Track Claude Code usage, estimate costs, and identify patterns across your development sessions.
## Table of Contents
1. [Why Monitor Sessions](#why-monitor-sessions)
2. [Session Search & Resume](#session-search--resume)
3. [Setting Up Session Logging](#setting-up-session-logging)
4. [Analyzing Session Data](#analyzing-session-data)
5. [Cost Tracking](#cost-tracking)
6. [Activity Monitoring](#activity-monitoring)
7. [External Monitoring Tools](#external-monitoring-tools)
8. [Proxying Claude Code](#proxying-claude-code)
9. [Patterns & Best Practices](#patterns--best-practices)
10. [Limitations](#limitations)
---
## Why Monitor Sessions
Claude Code usage can accumulate quickly, especially in active development. Monitoring helps you:
- **Understand costs**: Estimate API spend before invoices arrive
- **Identify patterns**: See which tools you use most, which files get edited repeatedly
- **Optimize workflow**: Find inefficiencies (e.g., repeatedly reading the same large file)
- **Track projects**: Compare usage across different codebases
- **Team visibility**: Aggregate usage for team budgeting (when combining logs)
---
## Session Search & Resume
After weeks of using Claude Code, finding past conversations becomes challenging. This section covers native options and community tools.
### Native Commands
| Command | Use Case |
|---------|----------|
| `claude -c` / `claude --continue` | Resume most recent session |
| `claude -r <id>` / `claude --resume <id>` | Resume specific session by ID |
| `claude --resume` | Interactive session picker |
Sessions are stored locally at `~/.claude/projects/<project>/` as JSONL files.
### Community Tools Comparison
| Tool | Install | List Speed | Search Speed | Dependencies | Resume Command |
|------|---------|------------|--------------|--------------|----------------|
| **session-search.sh** (this repo) | Copy script | **10ms** | **400ms** | None (bash) | ✅ Displayed |
| claude-conversation-extractor | `pip install` | 230ms | 1.7s | Python | ❌ |
| claude-code-transcripts | `uvx` | N/A | N/A | Python | ❌ |
| ran CLI | `npm -g` | N/A | Fast | Node.js | ❌ (commands only) |
### Recommended: session-search.sh
Zero-dependency bash script optimized for speed with ready-to-use resume commands.
**Install:**
```bash
cp examples/scripts/session-search.sh ~/.claude/scripts/cs
chmod +x ~/.claude/scripts/cs
echo "alias cs='~/.claude/scripts/cs'" >> ~/.zshrc
source ~/.zshrc
```
**Usage:**
```bash
cs # List 10 most recent sessions (~15ms)
cs "authentication" # Single keyword search (~400ms)
cs "Prisma migration" # Multi-word AND search (both must match)
cs -n 20 # Show 20 results
cs -p myproject "bug" # Filter by project name
cs --since 7d # Sessions from last 7 days
cs --since today # Today's sessions only
cs --json "api" | jq . # JSON output for scripting
cs --rebuild # Force index rebuild
```
**Output:**
```
2026-01-15 08:32 │ my-project │ Implement OAuth flow for...
claude --resume 84287c0d-8778-4a8d-abf1-eb2807e327a8
2026-01-14 21:13 │ other-project │ Fix database migration...
claude --resume 1340c42e-eac5-4181-8407-cc76e1a76219
```
Copy-paste the `claude --resume` command to continue any session.
### How It Works
1. **Index mode** (no filters): Uses cached TSV index. Auto-refreshes when sessions change. ~15ms lookup.
2. **Search mode** (with keyword/filters): Full-text search with 3s timeout. Multi-word queries use AND logic.
3. **Filters**: `--project` (substring match), `--since` (supports `today`, `yesterday`, `7d`, `YYYY-MM-DD`)
4. **Output**: Human-readable by default, `--json` for scripting. Excludes agent/subagent sessions.
### Alternative: Python Tools
If you prefer richer features (HTML export, multiple formats):
```bash
# Install
pip install claude-conversation-extractor
# Interactive UI
claude-start
# Direct search
claude-search "keyword"
# Export to markdown
claude-extract --format markdown
```
See [session-search.sh](../examples/scripts/session-search.sh) for the complete script.
---
### Session Resume Limitations & Cross-Folder Migration
**TL;DR**: Native `--resume` is limited to the current working directory by design. For cross-folder migration, use manual filesystem operations (recommended) or community automation tools (untested).
#### Why Resume is Directory-Scoped
Claude Code stores sessions at `~/.claude/projects/<encoded-path>/` where `<encoded-path>` is derived from your project's absolute path. For example:
- Project at `/home/user/myapp` → Sessions in `~/.claude/projects/-home-user-myapp-/`
- Project moved to `/home/user/projects/myapp` → Claude looks for `~/.claude/projects/-home-user-projects-myapp-/` (different directory)
**Design rationale**: Sessions store absolute file paths, project-specific context (MCP server configs, `.claudeignore` rules, environment variables). Cross-folder resume would require path rewriting and context validation, which isn't implemented yet.
**Related**: GitHub issue [#1516](https://github.com/anthropics/claude-code/issues/1516) tracks community requests for native cross-folder support.
#### Manual Migration (Recommended)
**When moving a project folder:**
```bash
# Before moving project
cd ~/.claude/projects/
ls -la # Note the current encoded path
# Move your project
mv /old/location/myapp /new/location/myapp
# Rename session directory to match new path
cd ~/.claude/projects/
mv -- -old-location-myapp- -new-location-myapp-
# Verify
cd /new/location/myapp
claude --continue # Should resume successfully
```
**When forking sessions to a new project:**
```bash
# Copy session files (preserves original)
cd ~/.claude/projects/
cp -n ./-source-project-/*.jsonl ./-target-project-/
# Copy subagents directory if exists
if [ -d ./-source-project-/subagents ]; then
cp -r ./-source-project-/subagents ./-target-project-/
fi
# Resume in target project
cd /path/to/target/project
claude --continue
```
#### ⚠️ Migration Risks & Caveats
**Before migrating sessions, verify compatibility:**
| Risk | Impact | Mitigation |
|------|--------|------------|
| **Hardcoded secrets** | Credentials exposed in new context | Audit `.jsonl` files before migration, redact if needed |
| **Absolute paths** | File references break if paths differ | Verify paths exist in target, or accept broken references |
| **MCP server configs** | Source MCP servers missing in target | Install matching MCP servers before resuming |
| **`.claudeignore` rules** | Different ignore patterns | Review differences, merge if needed |
| **Environment variables** | `process.env` context mismatch | Check `.env` files compatibility |
**When NOT to migrate sessions:**
- Conflicting dependencies (e.g., different Node.js versions, package managers)
- Database state differences (migrations applied in source, not in target)
- Authentication context (API tokens, OAuth sessions specific to source project)
- Security boundaries (migrating from private to public repo)
#### Community Automation Tool
**claude-migrate-session** by Jim Weller (inspired by Alexis Laporte) automates the manual process above:
- **Repository**: [jimweller/dotfiles](https://github.com/jimweller/dotfiles/tree/main/dotfiles/claude-code/skills/claude-migrate-session)
- **Features**: Global search with filtering, preserves `.jsonl` + subagents, uses ripgrep for performance
- **Status**: Personal dotfiles (0 stars/forks as of Feb 2026), limited adoption
- **Command**: `/claude-migrate-session <source> <target>`
**⚠️ Caveat**: This tool has minimal community testing. The manual approach is safer and gives you explicit control over what gets migrated. Test thoroughly before using in production workflows.
**Use cases for migration:**
- Forking prototype work into production codebase
- Moving debugging session to isolated test repository
- Continuing architecture discussion in a new project
#### Alternative: Entire CLI Session Portability
**Native limitation**: Claude Code's `--resume` is tied to absolute file paths, breaking on folder moves.
**Entire CLI solution**: Checkpoints are **path-agnostic**, enabling true session portability across project locations.
**How it works:**
```bash
# In source project
cd /old/location/myapp
entire capture --agent="claude-code"
[... work in Claude Code ...]
entire checkpoint --name="migration-complete"
# Move project to new location
mv /old/location/myapp /new/location/myapp
# Resume in target (works because Entire stores relative paths)
cd /new/location/myapp
entire resume --checkpoint="migration-complete"
claude --continue # Resumes with full context
```
**Why Entire checkpoints are portable:**
| Aspect | Native `--resume` | Entire CLI |
|--------|-------------------|-----------|
| **Path storage** | Absolute paths in JSONL | Relative paths in checkpoints |
| **Cross-folder** | Breaks (different project encoding) | Works (path-agnostic) |
| **Context preservation** | Prompt history only | Prompts + reasoning + file states |
| **Agent handoffs** | No | Yes (between Claude/Gemini) |
**When to use Entire over manual migration:**
- ✅ Frequent project moves/forks
- ✅ Multi-agent workflows (Claude → Gemini handoffs)
- ✅ Session replay for debugging (rewind to exact state)
- ✅ Governance (approval gates on resume)
**Trade-off**: Adds tool dependency + storage overhead (~5-10% project size).
> **Full docs**: [AI Traceability Guide](./ai-traceability.md#51-entire-cli)
---
### Multi-Agent Orchestration Monitoring
For monitoring multiple concurrent Claude Code instances via external orchestrators (Gas Town, multiclaude), see:
- **agent-chat** (https://github.com/justinabrahms/agent-chat): Real-time Slack-like UI for agent communications
- **Architecture guide**: `guide/ai-ecosystem.md` Section 8.1 - Multi-Agent Orchestration Systems
**Architecture pattern** (for custom implementations):
1. Hook logs Task agent spawns: `.claude/hooks/multi-agent-logger.sh`
2. Store in SQLite: `~/.claude/logs/agents.db` (parent_id, child_id, timestamp, task)
3. Stream via SSE: Simple Go/Node HTTP server
4. Dashboard: React/HTML consuming SSE stream
**Native Claude Code monitoring** (this guide):
- Session search: `session-search.sh` (see [Session Search & Resume](#session-search--resume))
- Activity logs: `session-logger.sh` hook (see [Setting Up Session Logging](#setting-up-session-logging))
- Stats analysis: `session-stats.sh` (see [Analyzing Session Data](#analyzing-session-data))
**When to use external orchestrator monitoring**:
- Running Gas Town or multiclaude with 5+ concurrent agents
- Need real-time visibility into agent coordination
- Debugging orchestration failures (agent conflicts, merge issues)
**When native monitoring suffices**:
- Single Claude Code session or `--delegate` with <3 subagents
- Post-hoc analysis (logs, stats) is enough
- Budget/complexity constraints
---
## Setting Up Session Logging
### 1. Install the Logger Hook
Copy the session logger to your hooks directory:
```bash
# Create hooks directory if needed
mkdir -p ~/.claude/hooks
# Copy the logger (from this repo's examples)
cp examples/hooks/bash/session-logger.sh ~/.claude/hooks/
chmod +x ~/.claude/hooks/session-logger.sh
```
### 2. Register in Settings
Add to `~/.claude/settings.json`:
```json
{
"hooks": {
"PostToolUse": [
{
"type": "command",
"command": "~/.claude/hooks/session-logger.sh"
}
]
}
}
```
### 3. Verify Installation
Run a few Claude Code commands, then check logs:
```bash
ls ~/.claude/logs/
# Should see: activity-2026-01-14.jsonl
# View recent entries
tail -5 ~/.claude/logs/activity-$(date +%Y-%m-%d).jsonl | jq .
```
### Configuration Options
| Environment Variable | Default | Description |
|---------------------|---------|-------------|
| `CLAUDE_LOG_DIR` | `~/.claude/logs` | Where to store logs |
| `CLAUDE_LOG_TOKENS` | `true` | Enable token estimation |
| `CLAUDE_SESSION_ID` | auto-generated | Custom session identifier |
---
## Analyzing Session Data
### Using session-stats.sh
```bash
# Copy the script
cp examples/scripts/session-stats.sh ~/.local/bin/
chmod +x ~/.local/bin/session-stats.sh
# Today's summary
session-stats.sh
# Last 7 days
session-stats.sh --range week
# Specific date
session-stats.sh --date 2026-01-14
# Filter by project
session-stats.sh --project my-app
# Machine-readable output
session-stats.sh --json
```
### Sample Output
```
═══════════════════════════════════════════════════════════
Claude Code Session Statistics - today
═══════════════════════════════════════════════════════════
Summary
Total operations: 127
Sessions: 3
Token Usage
Input tokens: 45,230
Output tokens: 12,450
Total tokens: 57,680
Estimated Cost (Sonnet rates)
Input: $0.1357
Output: $0.1868
Total: $0.3225
Tools Used
Edit: 45
Read: 38
Bash: 24
Grep: 12
Write: 8
Projects
my-app: 89
other-project: 38
```
### Log Format
Each log entry is a JSON object:
```json
{
"timestamp": "2026-01-14T15:30:00Z",
"session_id": "1705234567-12345",
"tool": "Edit",
"file": "src/components/Button.tsx",
"project": "my-app",
"tokens": {
"input": 350,
"output": 120,
"total": 470
}
}
```
---
## Cost Tracking
### Token Estimation Method
The logger estimates tokens using a simple heuristic: **~4 characters per token**. This is approximate and tends to slightly overestimate.
### Cost Rates
Default rates are for Claude Sonnet. Adjust via environment variables:
```bash
# Sonnet rates (default)
export CLAUDE_RATE_INPUT=0.003 # $3/1M tokens
export CLAUDE_RATE_OUTPUT=0.015 # $15/1M tokens
# Opus rates (if using Opus)
export CLAUDE_RATE_INPUT=0.015 # $15/1M tokens
export CLAUDE_RATE_OUTPUT=0.075 # $75/1M tokens
# Haiku rates
export CLAUDE_RATE_INPUT=0.00025 # $0.25/1M tokens
export CLAUDE_RATE_OUTPUT=0.00125 # $1.25/1M tokens
```
### Budget Alerts (Manual Pattern)
Add to your shell profile for daily budget warnings:
```bash
# ~/.zshrc or ~/.bashrc
claude_budget_check() {
local cost=$(session-stats.sh --json 2>/dev/null | jq -r '.summary.estimated_cost.total // 0')
local threshold=5.00 # $5 daily budget
if (( $(echo "$cost > $threshold" | bc -l) )); then
echo "⚠️ Claude Code daily spend: \$$cost (threshold: \$$threshold)"
fi
}
# Run on shell start
claude_budget_check
```
---
## Activity Monitoring
Cost tracking tells you *how much* you spend. Activity monitoring tells you *what Claude Code actually did*: which files it read, which commands it ran, which URLs it fetched. This is the audit layer.
### Session JSONL: The Ground Truth
Every tool call Claude Code makes is recorded in the session JSONL files at `~/.claude/projects/<project>/`. Each entry with `type: "assistant"` contains a `content` array where `type: "tool_use"` blocks document every action.
```bash
# Find your session files
ls ~/.claude/projects/-$(pwd | tr '/' '-')-/
# Inspect tool calls in a session
cat ~/.claude/projects/-your-project-/SESSION_ID.jsonl | \
jq 'select(.type == "assistant") | .message.content[]? | select(.type == "tool_use") | {tool: .name, input: .input}'
```
### What Tool Calls Reveal
| Tool | What It Exposes |
|------|----------------|
| `Read` | Files accessed (path, line range) |
| `Write` / `Edit` | Files modified (path, content delta) |
| `Bash` | Commands executed (full command string) |
| `WebFetch` | URLs fetched (may include data sent in POST) |
| `Task` | Subagent spawns (prompt passed to sub-model) |
| `Glob` / `Grep` | Search patterns and scope |
### Practical Audit Queries
```bash
# All files read in a session
SESSION=~/.claude/projects/-your-project-/SESSION_ID.jsonl
jq 'select(.type == "assistant") | .message.content[]? | select(.type == "tool_use" and .name == "Read") | .input.file_path' "$SESSION"
# All bash commands executed
jq 'select(.type == "assistant") | .message.content[]? | select(.type == "tool_use" and .name == "Bash") | .input.command' "$SESSION"
# All URLs fetched
jq 'select(.type == "assistant") | .message.content[]? | select(.type == "tool_use" and .name == "WebFetch") | .input.url' "$SESSION"
# Count tool usage by type
jq -r 'select(.type == "assistant") | .message.content[]? | select(.type == "tool_use") | .name' "$SESSION" | sort | uniq -c | sort -rn
```
### Sensitive Patterns to Watch
These tool call patterns are worth flagging in automated audits:
| Pattern | Risk | Detection |
|---------|------|-----------|
| `Read` on `.env`, `*.pem`, `id_rsa` | Credential access | `jq '... | select(.input.file_path | test("\\.(env|pem|key)$"))'` |
| `Bash` with `rm -rf`, `git push --force` | Destructive action | `jq '... | select(.input.command | test("rm -rf\|force-push"))'` |
| `WebFetch` on external URLs | Data exfiltration risk | `jq '... | select(.name == "WebFetch") | .input.url'` |
| `Write` on files outside project root | Scope creep | Check paths against working directory |
> **Security context**: Claude Code operates read-write on your filesystem with your user permissions. The JSONL audit trail is your record of what happened. For teams, consider syncing these logs to immutable storage.
---
## External Monitoring Tools
Beyond the hook-based approach above, the community has built purpose-specific tools. This is a factual snapshot as of early 2026.
| Tool | Type | What It Does | Install |
|------|------|-------------|---------|
| **ccusage** | CLI / TUI | Cost tracking from JSONL the de-facto reference for pricing data. ~10K GitHub stars. | `npm i -g ccusage` |
| **claude-code-otel** | OpenTelemetry exporter | Emits spans to any OTEL collector. Integrates with Prometheus + Grafana dashboards. Enterprise-focused. | `npm i -g claude-code-otel` |
| **Akto** | SaaS / self-hosted | API security guardrails + audit trail. Intercepts at the API level, flags policy violations. | [akto.io](https://akto.io) |
| **MLflow Tracing** | SDK integration | Structured traces (tool usage, latency, inputs/outputs). Requires wrapping calls in Python. | `pip install mlflow` |
| **ccboard** | TUI + Web | Unified dashboard for sessions, costs, stats. Activity/audit tab in development. | `cargo install ccboard` |
### Decision Guide
```
Want cost numbers fast? → ccusage (CLI, 0 config)
Need enterprise audit trail? → claude-code-otel + Grafana or Akto
Already using MLflow for ML? → MLflow tracing integration
Want a persistent TUI/Web UI? → ccboard
```
### ccusage
```bash
npm i -g ccusage
ccusage # Today's usage
ccusage --days 7 # Last 7 days
```
Reads directly from `~/.claude/projects/**/*.jsonl`. No API keys, no data sent externally. Source: [github.com/ryoppippi/ccusage](https://github.com/ryoppippi/ccusage).
### claude-code-otel
Exports Claude Code activity as OpenTelemetry spans:
```bash
npm i -g claude-code-otel
claude-code-otel --collector http://localhost:4318
```
Spans include tool name, duration, token counts. Plug into any OTEL-compatible backend (Jaeger, Tempo, Datadog). Source: [github.com/badger-99/claude-code-otel](https://github.com/badger-99/claude-code-otel).
### ccboard
```bash
cargo install ccboard
ccboard # Launch TUI
ccboard --web # Launch Web UI (localhost:3000)
```
Source: [github.com/FlorianBruniaux/ccboard](https://github.com/FlorianBruniaux/ccboard). An Activity tab covering file access, bash commands, and network calls is planned (see `docs/resource-evaluations/ccboard-activity-module-plan.md`).
---
## Proxying Claude Code
A common question: "Can I run Proxyman/Charles to see what Claude Code sends to Anthropic?"
**Short answer**: Not directly. Here's why, and what works instead.
### Why System Proxies Don't Work
Claude Code is a Node.js process. By default, Node.js ignores system-level proxy settings (`HTTP_PROXY`, `HTTPS_PROXY`) it uses its own TLS stack and doesn't read macOS/Windows proxy configurations.
Additionally, even if traffic flows through your proxy, the TLS certificate mismatch causes Claude Code to fail (`CERT_UNTRUSTED`).
### Option 1: Trust a MITM Certificate (Proxyman / Charles)
Force Node.js to trust your proxy's CA certificate:
```bash
# Export Proxyman's CA cert (File → Export → Root Certificate)
# Then point Node.js at it:
export NODE_EXTRA_CA_CERTS="/path/to/proxyman-ca.pem"
# Start Claude Code — traffic will now route through Proxyman
claude
```
Same approach works for Charles: `Help → SSL Proxying → Export Charles Root Certificate`.
**Caveats**:
- Some Claude Code versions use certificate pinning for `api.anthropic.com` this may still fail
- This approach requires a running Proxyman/Charles instance listening on the configured port
### Option 2: Redirect API Traffic with ANTHROPIC_API_URL
Point Claude Code at a local interceptor instead of `api.anthropic.com`:
```bash
export ANTHROPIC_API_URL="http://localhost:8080"
claude
```
Run any HTTP proxy/logger on port 8080 that forwards to `https://api.anthropic.com`. This bypasses TLS entirely for the Claude Code proxy hop.
**Use cases**: Logging request payloads, injecting headers, rate-limiting locally, replaying requests.
### Option 3: mitmproxy (Recommended)
[mitmproxy](https://mitmproxy.org) is the cleanest open-source solution. It provides a scriptable HTTPS proxy with a web UI and terminal interface.
```bash
# Install
brew install mitmproxy # macOS
# or: pip install mitmproxy
# Start transparent proxy on port 8080
mitmproxy --listen-port 8080
# In a new terminal, point Claude Code at it
export NODE_EXTRA_CA_CERTS="$(python3 -c 'import mitmproxy.certs; print(mitmproxy.certs.Cert.default_ca_path())')"
export HTTPS_PROXY="http://localhost:8080"
claude
```
The mitmproxy web UI (`mitmweb`) at `http://localhost:8081` shows full request/response bodies including the JSON payloads Claude Code sends to Anthropic.
**What you'll see**: System prompt, user messages, tool definitions, tool results, model parameters.
### Option 4: Minimal Python Logging Proxy
For a zero-dependency approach:
```python
# proxy.py — simple HTTPS logging proxy
from http.server import HTTPServer, BaseHTTPRequestHandler
import urllib.request, json, sys
TARGET = "https://api.anthropic.com"
class LoggingProxy(BaseHTTPRequestHandler):
def do_POST(self):
length = int(self.headers["Content-Length"])
body = self.rfile.read(length)
print(json.dumps(json.loads(body), indent=2)) # Log request
# Forward to Anthropic...
HTTPServer(("localhost", 8080), LoggingProxy).serve_forever()
```
```bash
python3 proxy.py &
export ANTHROPIC_API_URL="http://localhost:8080"
claude
```
> **Privacy note**: Proxied traffic includes everything in the conversation context — file contents Claude has read, your code, any secrets it encountered. Handle proxy logs accordingly.
---
## Patterns & Best Practices
### 1. Weekly Review
Set a calendar reminder to review weekly stats:
```bash
session-stats.sh --range week
```
Look for:
- Unusually high token usage days
- Repeated operations on same files (inefficiency signal)
- Project distribution (where time is spent)
### 2. Per-Project Tracking
Use `CLAUDE_SESSION_ID` to tag sessions by project:
```bash
export CLAUDE_SESSION_ID="project-myapp-$(date +%s)"
claude
```
### 3. Team Aggregation
For team-wide tracking, sync logs to shared storage:
```bash
# Example: sync to S3 daily
aws s3 sync ~/.claude/logs/ s3://company-claude-logs/$(whoami)/
```
Then aggregate with:
```bash
# Download all team logs
aws s3 sync s3://company-claude-logs/ /tmp/team-logs/
# Combine and analyze
cat /tmp/team-logs/*/activity-$(date +%Y-%m-%d).jsonl | \
jq -s 'group_by(.project) | map({project: .[0].project, total_tokens: [.[].tokens.total] | add})'
```
### 4. Log Rotation
Logs accumulate over time. Add cleanup to cron:
```bash
# Clean logs older than 30 days
find ~/.claude/logs -name "*.jsonl" -mtime +30 -delete
```
---
## Limitations
### What This Monitoring CANNOT Do
| Limitation | Reason |
|------------|--------|
| **Exact token counts** | Claude Code CLI doesn't expose API token metrics |
| **TTFT (Time to First Token)** | Hook runs after tool completes, not during streaming |
| **Real-time streaming metrics** | No hook event during response generation |
| **Actual API costs** | Token estimates are heuristic, not from billing |
| **Model selection** | Log doesn't capture which model was used per request |
| **Context window usage** | No visibility into current context percentage |
### Accuracy Notes
- **Token estimates**: ~15-25% variance from actual billing
- **Cost estimates**: Use as directional guidance, not accounting
- **Session boundaries**: Sessions are approximated by ID, not exact API sessions
### What You CAN Trust
- **Tool usage counts**: Exact count of each tool invocation
- **File access patterns**: Which files were touched
- **Relative comparisons**: Day-to-day/project-to-project trends
- **Operation timing**: When tools were used (timestamp)
---
## Related Resources
- [Session Search Script](../examples/scripts/session-search.sh) - Fast session search & resume
- [Session Logger Hook](../examples/hooks/bash/session-logger.sh)
- [Stats Analysis Script](../examples/scripts/session-stats.sh)
- [Third-Party Tools](./third-party-tools.md) - Community GUIs, TUIs, and dashboards (ccusage, ccburn, claude-code-viewer)
- [Data Privacy Guide](./data-privacy.md) - What data leaves your machine
- [Cost Optimization](./ultimate-guide.md#cost-optimization) - Tips to reduce spend