tools-only Token Estimation Reference
Detailed heuristics for estimating context window token costs from observable signals. These are approximations — actual tokenization varies by model.
Character-to-Token Ratios
| Content Type | Ratio (chars/token) | Notes |
|---|---|---|
| English prose | ~4.0 | Standard text |
| Code (TypeScript/JS) | ~3.5 | More symbols, shorter words |
| Code (Python) | ~3.8 | Slightly more readable |
| Code (Bicep/ARM) | ~3.2 | Verbose resource declarations |
| JSON data | ~3.0 | Keys, braces, quotes overhead |
| Markdown | ~3.8 | Mix of prose and formatting |
| YAML | ~3.5 | Indentation-heavy |
VS Code Copilot System Prompt Costs
These components are always present in the context window:
| Component | Estimated Tokens | Source |
|---|---|---|
| Base system prompt | ~2,000 | VS Code internals |
| Per tool definition | ~50-100 | JSON schema per tool |
| Per handoff definition | ~30-50 | Agent metadata |
| Conversation history (per turn) | ~200-2,000+ | Depends on turn size |
| File attachment | ~file_size / 3.5 | Attached file content |
| Workspace info | ~200-500 | Project structure |
| Instruction file (when matched) | ~file_size / 4 | Full file content |
Agent Definition Context Cost
To estimate the fixed context cost of an agent:
base_cost = 2000 # system prompt overhead
tool_cost = num_tools * 75 # average per tool
handoff_cost = num_handoffs * 40
body_cost = body_chars / 4
instruction_cost = sum(matched_instruction_chars / 4)
total_fixed = base_cost + tool_cost + handoff_cost + body_cost + instruction_cost
Model Context Limits
| Model | Context Window | Practical Limit (80%) |
|---|---|---|
| Claude Opus 4.6 | 200K tokens | ~160K tokens |
| GPT-5.3-Codex | 128K tokens | ~102K tokens |
| gpt-4o-mini | 128K tokens | ~102K tokens |
| Claude Sonnet 4 | 200K tokens | ~160K tokens |
The "practical limit" accounts for output generation headroom. Quality typically degrades before hitting the hard limit.
Latency-to-Context Correlation
Based on empirical observation of streaming responses:
| Model | Latency < 5s | 5-10s | 10-20s | 20-30s | > 30s |
|---|---|---|---|---|---|
| Claude Opus 4.6 | < 20K in | 20-60K in | 60-120K in | 120-160K in | Near limit |
| GPT-5.3-Codex | < 15K in | 15-40K in | 40-80K in | 80-100K in | Near limit |
| gpt-4o-mini | < 10K in | 10-30K in | 30-60K in | 60-80K in | Near limit |
"in" = input tokens. These are rough bands — output length, streaming overhead, and server load all affect latency.
Warning Thresholds
| Metric | Yellow | Red |
|---|---|---|
| Fixed agent context cost | > 5,000 tokens | > 10,000 tokens |
| Instructions loaded per request | > 5 files | > 10 files |
| Conversation turns without hand-off | > 15 turns | > 25 turns |
| Single file read | > 5,000 tokens | > 15,000 tokens |
| Cumulative file reads per session | > 30,000 tokens | > 60,000 tokens |