# Send Embeddings to your agent Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually. ## Fast path - Download the package from Yavira. - Extract it into a folder your agent can access. - Paste one of the prompts below and point your agent at the extracted folder. ## Suggested prompts ### New install ```text I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete. ``` ### Upgrade existing ```text I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run. ``` ## Machine-readable fields ```json { "schemaVersion": "1.0", "item": { "slug": "embeddings", "name": "Embeddings", "source": "tencent", "type": "skill", "category": "开发工具", "sourceUrl": "https://clawhub.ai/ivangdavila/embeddings", "canonicalUrl": "https://clawhub.ai/ivangdavila/embeddings", "targetPlatform": "OpenClaw" }, "install": { "downloadUrl": "/downloads/embeddings", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=embeddings", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "packageFormat": "ZIP package", "primaryDoc": "SKILL.md", "includedAssets": [ "SKILL.md", "chunking.md", "providers.md", "search.md", "storage.md" ], "downloadMode": "redirect", "sourceHealth": { "source": "tencent", "slug": "embeddings", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-05-02T22:04:03.741Z", "expiresAt": "2026-05-09T22:04:03.741Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=embeddings", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=embeddings", "contentDisposition": "attachment; filename=\"embeddings-1.0.0.zip\"", "redirectLocation": null, "bodySnippet": null, "slug": "embeddings" }, "scope": "item", "summary": "Item download looks usable.", "detail": "Yavira can redirect you to the upstream package for this item.", "primaryActionLabel": "Download for OpenClaw", "primaryActionHref": "/downloads/embeddings" }, "validation": { "installChecklist": [ "Use the Yavira download entry.", "Review SKILL.md after the package is downloaded.", "Confirm the extracted package contains the expected setup assets." ], "postInstallChecks": [ "Confirm the extracted package includes the expected docs or setup files.", "Validate the skill or prompts are available in your target agent workspace.", "Capture any manual follow-up steps the agent could not complete." ] } }, "links": { "detailUrl": "https://openagent3.xyz/skills/embeddings", "downloadUrl": "https://openagent3.xyz/downloads/embeddings", "agentUrl": "https://openagent3.xyz/skills/embeddings/agent", "manifestUrl": "https://openagent3.xyz/skills/embeddings/agent.json", "briefUrl": "https://openagent3.xyz/skills/embeddings/agent.md" } } ``` ## Documentation ### When to Use User wants to convert text/images to vectors, build semantic search, or integrate embeddings into applications. ### Quick Reference TopicFileProvider comparison & selectionproviders.mdChunking strategies & codechunking.mdVector database patternsstorage.mdSearch & retrieval tuningsearch.md ### Core Capabilities Generate embeddings — Call provider APIs (OpenAI, Cohere, Voyage, local models) Chunk content — Split documents with overlap, semantic boundaries, token limits Store vectors — Insert into Pinecone, Weaviate, Qdrant, pgvector, Chroma Similarity search — Query with top-k, filters, hybrid search Batch processing — Handle large datasets with rate limiting and retries Model comparison — Evaluate embedding quality for specific use cases ### Decision Checklist Before recommending approach, ask: What content type? (text, code, images, multimodal) Volume and update frequency? Latency requirements? (real-time vs batch) Budget constraints? (API costs vs self-hosted) Existing infrastructure? (cloud provider, database) ### Critical Rules Same model everywhere — Query embeddings MUST use identical model as document embeddings Normalize before storage — Most similarity metrics assume unit vectors Chunk with overlap — 10-20% overlap prevents context loss at boundaries Batch API calls — Never embed one item at a time in production Cache embeddings — Regenerating is expensive; store with source hash Monitor dimensions — Higher isn't always better; 768-1536 is usually optimal ### Provider Quick Selection NeedProviderWhyBest quality, any costOpenAI text-embedding-3-largeTop benchmarksCost-sensitiveOpenAI text-embedding-3-small5x cheaper, 80% qualityMultilingualCohere embed-multilingual-v3100+ languagesCode/technicalVoyage voyage-code-2Optimized for codePrivacy/offlineLocal (e5, bge, nomic)No data leaves machineImagesOpenAI CLIP, Cohere multimodalCross-modal search ### Common Patterns # Batch embedding with retry def embed_batch(texts, model="text-embedding-3-small"): results = [] for chunk in batched(texts, 100): # API limit response = client.embeddings.create(input=chunk, model=model) results.extend([e.embedding for e in response.data]) return results # Similarity search with filter results = index.query( vector=query_embedding, top_k=10, filter={"category": "technical"}, include_metadata=True ) ## Trust - Source: tencent - Verification: Indexed source record - Publisher: ivangdavila - Version: 1.0.0 ## Source health - Status: healthy - Item download looks usable. - Yavira can redirect you to the upstream package for this item. - Health scope: item - Reason: direct_download_ok - Checked at: 2026-05-02T22:04:03.741Z - Expires at: 2026-05-09T22:04:03.741Z - Recommended action: Download for OpenClaw ## Links - [Detail page](https://openagent3.xyz/skills/embeddings) - [Send to Agent page](https://openagent3.xyz/skills/embeddings/agent) - [JSON manifest](https://openagent3.xyz/skills/embeddings/agent.json) - [Markdown brief](https://openagent3.xyz/skills/embeddings/agent.md) - [Download page](https://openagent3.xyz/downloads/embeddings)