Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/secondlifes/code-intel/minimize-latencynpx skills add SecondLifes/code-intel --skill minimize-latencygit clone --depth 1 https://github.com/SecondLifes/code-intelWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00063 | $0.00621 |
| Opus 5 | $0.00032 | $0.00311 |
| Sonnet 5 | $0.00013 | $0.00124 |
| Haiku 4.5 | $0.00006 | $0.00062 |
Grade A, and why
qdrant-minimize-latency scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to qdrant-minimize-latency — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scaling for Query Latency
Latency of a single query is determined by the slowest component in the query execution path. It is sometimes correlated with throughput, but not always — throughput and latency are opposite tuning directions.
Low latency optimization is aimed at utilising maximum resource saturation for a single query, while throughput optimization is aimed at minimizing per-query resource usage to allow more parallel queries.
Performance Tuning for Lower Latency
- Increase segment count to match CPU cores (
default_segment_number: 16) Minimizing latency - Keep quantized vectors and HNSW in RAM:
memory: pinnedon Qdrant 1.19 or newer,always_ram: trueon 1.18 or older - Reduce
hnsw_efat query time (trade recall for speed) Search params - Use local NVMe, avoid network-attached storage
Memory Pressure and Latency
RAM is the most critical resource for latency. If working set exceeds available RAM, OS cache eviction causes severe, sustained latency degradation.
- Vertical scale RAM first. Critical if working set >80%.
- Use quantization: scalar (4x reduction) or binary (16x reduction) Quantization
- Move payload indexes to disk if filtering is infrequent:
memory: coldon Qdrant 1.19 or newer,on_disk: trueon 1.18 or older On-disk payload index - Set
optimizer_cpu_budgetto limit background optimization CPUs - Schedule indexing: set high
indexing_thresholdduring peak hours
Vertical Scaling for Latency
More RAM and faster CPU directly reduce latency. See Vertical Scaling for node sizing guidelines.
What NOT to Do
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 42 lines · 63 tokens per session scan A 6a5d30b48f68
qdrant-minimize-latency is a skill published in the GitHub repository SecondLifes/code-intel (2 stars, last pushed 21d ago), licensed Apache-2.0. It adds 63 tokens to every session and 621 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to qdrant-minimize-latency, differing in 0 lines, and is treated as a copy.
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