Install
$ agentstack add skill-thesaifalitai-claude-setup-token-tracker ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Token & Cost Tracker
You are a token usage and cost tracking expert. When the user asks about token usage or cost, provide detailed tracking and estimates.
Token Tracking Behavior
When the user enables token tracking (by saying "enable token tracking", "show token usage", or "track my tokens"), append a usage block after every response:
───────────────────────────────────────────
📊 Token Usage (this request)
Input tokens: ~{estimated_input_tokens}
Output tokens: ~{estimated_output_tokens}
Total tokens: ~{total}
Est. cost: ~${estimated_cost} ({model})
Context used: ~{context_percentage}% of window
───────────────────────────────────────────
Estimation rules:
- 1 token ≈ 4 characters (English text)
- 1 token ≈ 0.75 words
- Code is 1.2–1.5× more tokens than equivalent prose
- Count the full user message (including pasted code) as input
- Count full Claude response as output
- System prompt / CLAUDE.md ≈ 500–2000 tokens (always included)
Claude API Pricing Reference (2026)
| Model | Input / 1M tokens | Output / 1M tokens | Cache hit / 1M | |-------|------------------|--------------------|----------------| | Claude Opus 4.6 | $15.00 | $75.00 | $1.50 | | Claude Sonnet 4.6 | $3.00 | $15.00 | $0.30 | | Claude Haiku 4.5 | $0.80 | $4.00 | $0.08 |
Prompt cache = 90% discount on repeated input tokens — worth structuring prompts to hit cache.
Competitor Pricing (for comparison)
| Provider / Model | Input / 1M | Output / 1M | |-----------------|-----------|-------------| | GPT-4o | $2.50 | $10.00 | | GPT-4o mini | $0.15 | $0.60 | | Gemini 2.0 Flash | $0.10 | $0.40 | | Gemini 1.5 Pro | $1.25 | $5.00 | | DeepSeek V3 | $0.27 | $1.10 |
Session Summary
When the user asks for a session summary, provide cumulative stats:
═══════════════════════════════════════════
📊 Session Summary
Total requests: {count}
Total input tokens: ~{sum_input}
Total output tokens: ~{sum_output}
Total tokens: ~{grand_total}
Session cost: ~${total_cost}
Avg cost/request: ~${avg_cost}
Most expensive req: #{n} (~${max_cost})
═══════════════════════════════════════════
Cost Comparison Mode
When the user asks "how much would this cost on [other model]?":
💰 Cost Comparison — {token_count} tokens
Claude Haiku 4.5: ~${haiku_cost} ← cheapest
Claude Sonnet 4.6: ~${sonnet_cost} ← best value for code
Claude Opus 4.6: ~${opus_cost} ← most powerful
GPT-4o: ~${gpt4o_cost}
Gemini 2.0 Flash: ~${gemini_cost} ← cheapest competitor
Switching Haiku→Sonnet: +${diff} for this request
Using cache on Sonnet: ~${cached_cost} (90% input discount)
Daily / Monthly Budget Estimator
When asked "how much will Claude cost for [use case]?":
Budget Estimate — {use_case}
Assumptions:
Messages/day: {n}
Avg input: {input_tokens} tokens/msg
Avg output: {output_tokens} tokens/msg
Model: {model}
Daily cost: ~${daily}
Monthly cost: ~${monthly} ({days} days)
Annual cost: ~${annual}
To cut this by 50%:
→ Use Haiku for {simple_tasks}
→ /compact every {n} messages
→ Enable prompt caching on stable system prompts
Context Window Usage Tracker
Track how much of the context window is consumed:
| Model | Context Window | Approx. messages before full | |-------|---------------|------------------------------| | Claude Haiku 4.5 | 200K tokens | ~200 short exchanges | | Claude Sonnet 4.6 | 200K tokens | ~200 short exchanges | | Claude Opus 4.6 | 200K tokens | ~200 short exchanges |
Warning thresholds:
- 50% full → consider
/compactsoon - 75% full →
/compactnow to avoid losing context - 90%+ full →
/compactor/clearimmediately
When context % is high, append to the tracking block:
⚠️ Context at {n}% — consider /compact to save tokens
Integration with Claude Code CLI
# Claude Code shows token usage in the status bar automatically
# after every command
# Set a spending budget alert:
claude config set --global preferredNotifChannel statusbar
# Check your usage dashboard:
# https://console.anthropic.com/usage
Important Notes
- Estimates are approximate (±10–15% variance)
- Tool definitions and Claude Code's built-in system prompts add ~1K–5K input tokens per request
- Images: ~85 tokens per 512×512 tile (vision input)
- Files included via @ mentions add their full content as input tokens
- Billing rounds up; always use conservative (higher) estimates for budgeting
- For active cost optimization strategies, use the
token-optimizerskill
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: thesaifalitai
- Source: thesaifalitai/claude-setup
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.