Inception Token Optimizer#
Reduce Inception API token consumption through prompt engineering, context management, and budget enforcement.
Free-Tier Limits (Inception Labs)#
MetricCapRequests/min100Input tokens/min100,000Output tokens/min10,000
Core Strategies#
1. Prompt Compression#
- Remove redundant instructions, filler words, and repeated context.
- Use short system prompts: "Concise answers. French." beats a 200-word persona block.
- Avoid re-sending unchanged context — only send deltas.
- Ask for short replies: "Réponds en < 100 mots."
2. Context Pruning#
- Before sending, estimate tokens:
len(text) // 4 (rough heuristic).
- If total context > target budget, drop oldest messages and replace with a 1-2 sentence summary.
- Use
references/pruning-strategies.md for detailed patterns.
3. Caching#
- Identical prompts → reuse previous response. Do not re-call.
- Hash the prompt; if seen recently (within session), return cached reply.
scripts/lru_cache.py provides a drop-in LRU cache (256 items default).
4. Model Selection#
- Use cheaper/faster models for simple tasks (summarisation, classification).
- Reserve Mercury (or flagship) for complex reasoning only.
- Batch trivial queries into a single prompt instead of multiple calls.
5. Output Budgeting#
- Set
max_tokens explicitly — never leave it open-ended.
- Target 150-200 output tokens for conversational replies.
- Use
temperature=0.7 to reduce verbose wandering.
Token Budget Guard#
scripts/token_bucket.py enforces per-minute caps using a sliding window:
python
from scripts.token_bucket import TokenBucket
bucket = TokenBucket(req_per_min=100, in_tok_per_min=100_000, out_tok_per_min=10_000)
bucket.wait_for_slot(in_tokens=500, out_tokens=200)
# proceed with API call
Blocks until a slot is available. Use before every Inception API call.
When to Use This Skill#
- Before sending a prompt to Inception → compress & prune first.
- When monitoring costs → check token estimates.
- When near free-tier limits → activate budget guard.
- When building automation → integrate caching + bucket guard.