Optimize vector index performance across latency, recall, and memory tradeoffs.
Run in your terminal
Covers HNSW parameter tuning (M, efConstruction, efSearch) with benchmarking templates and automated recommendation logic based on vector count and target recall
Includes quantization strategies: scalar INT8, product quantization, binary quantization, and FP16 compression with memory estimation tools
Provides Qdrant collection configuration templates optimized for three scenarios: recall-focused, speed-fo
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionvector-index-tuningExecute the skills CLI command in your project's root directory to begin installation:
Package manager
npx skills add https://github.com/wshobson/agents --skill vector-index-tuningFetches vector-index-tuning from wshobson/agents and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate vector-index-tuning. Access via /vector-index-tuningin your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
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Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Package manager
npx skills add https://github.com/wshobson/agents --skill vector-index-tuningWorks with
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Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
wshobson/agents
wshobson/agents
wshobson/agents
davila7/claude-code-templates
intellectronica/agent-skills
am-will/codex-skills
Keeps context tight: vector-index-tuning is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added vector-index-tuning from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
vector-index-tuning reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for vector-index-tuning matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: vector-index-tuning is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for vector-index-tuning matched our evaluation — installs cleanly and behaves as described in the markdown.
vector-index-tuning is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: vector-index-tuning is the kind of skill you can hand to a new teammate without a long onboarding doc.
vector-index-tuning is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
vector-index-tuning reduced setup friction for our internal harness; good balance of opinion and flexibility.
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