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/indexing-performance-optimizationnpx skills add SecondLifes/code-intel --skill indexing-performance-optimizationgit 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 | $0.00078 | $0.01146 |
| Opus 5 | $0.00039 | $0.00573 |
| Sonnet 5 | $0.00016 | $0.00229 |
| Haiku 4.5 | $0.00008 | $0.00115 |
Grade A, and why
qdrant-indexing-performance-optimization 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-indexing-performance-optimization — 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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
What to Do When Qdrant Indexing Is Too Slow
Qdrant does NOT build HNSW indexes immediately. Small segments use brute-force until they exceed indexing_threshold_kb (default: 20 MB). Search during this window is slower by design, not a bug.
- Understand the indexing optimizer Indexing optimizer
Uploads/Ingestion Too Slow
Use when: upload or upsert API calls are slow. Identify bottleneck: client-side (network, batching) vs server-side (CPU, disk I/O)
For client-side, optimize batching and parallelism:
- Use batch upserts (64-256 points per request) Points API
- Use 2-4 parallel upload streams
For server-side, optimize Qdrant configuration and indexing strategy:
- Create more shards (3-12), each shard has an independent update worker Sharding
- Create payload indexes before HNSW builds (needed for filterable vector index) Payload index
Suitable for initial bulk load of large datasets:
- Disable HNSW during bulk load (set
indexing_threshold_kbvery high, restore after) Collection params - Setting
m=0to disable HNSW is legacy, use highindexing_threshold_kbinstead
Careful, fast unindexed upload might temporarily use more RAM and degrade search performance until optimizer catches up.
See https://skills.qdrant.tech/md/documentation/manage-data/bulk-upload/
Optimizer Stuck or Taking Too Long
Use when: optimizer running for hours, not finishing.
- Check actual progress via optimizations endpoint (v1.17+) Optimization monitoring
- Large merges and HNSW rebuilds legitimately take hours on big datasets
- Check CPU and disk I/O (HNSW is CPU-bound, merging is I/O-bound, HDD is not viable)
- If
optimizer_statusshows an error, check logs for disk full or corrupted segments
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 · 81 lines · 78 tokens per session scan A c4e47ccef61f
qdrant-indexing-performance-optimization is a skill published in the GitHub repository SecondLifes/code-intel (2 stars, last pushed 21d ago), licensed Apache-2.0. It adds 78 tokens to every session and 1,146 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to qdrant-indexing-performance-optimization, differing in 0 lines, and is treated as a copy.
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