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-`customer-onboarding` — Standard procedures and common customer questions
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**When to use skills vs. agent instructions:**
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- Use **skills** for knowledge that applies across multiple workflows or changes frequently
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- Use **agent instructions** for task-specific context that's unique to a single agent
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## Best Practices
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**Writing Effective Descriptions**
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-**Be specific and keyword-rich** — Instead of "Helps with SQL", write "Write optimized SQL queries for PostgreSQL, MySQL, and SQLite, including index recommendations and query plan analysis"
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-**Include activation triggers** — Mention specific words or phrases that should prompt the skill (e.g., "Use when the user mentions PDFs, forms, or document extraction")
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-**Keep it under 200 words** — Agents scan descriptions quickly; make every word count
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-**Keep descriptions actionable** — Instead of "Helps with SQL", write "Write optimized SQL queries for PostgreSQL, MySQL, and SQLite, including index recommendations and query plan analysis"
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**Skill Scope and Organization**
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-**One skill per domain** — A focused `sql-expert` skill works better than a broad `database-everything` skill
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-**Use markdown structure** — Headers, lists, and code blocks help the agent parse and follow instructions
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-**Test iteratively** — Run your workflow and check if the agent activates the skill when expected
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-**Limit to 5-10 skills per agent** — More skills = more decision overhead; start small and add as needed
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-**Split large skills** — If a skill exceeds 500 lines, break it into focused sub-skills
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**Content Structure**
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-**Use markdown formatting** — Headers, lists, and code blocks help agents parse and follow instructions
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-**Provide examples** — Show input/output pairs so agents understand expected behavior
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-**Be explicit about edge cases** — Don't assume agents will infer special handling
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**Testing and Iteration**
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-**Test activation** — Run your workflow and verify the agent loads the skill when expected
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-**Check for false positives** — Make sure skills aren't activating when they shouldn't
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-**Refine descriptions** — If a skill isn't loading when needed, add more keywords to the description
Copy file name to clipboardExpand all lines: apps/docs/content/docs/en/tools/airweave.mdx
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color="#6366F1"
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/>
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{/* MANUAL-CONTENT-START:intro */}
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[Airweave](https://airweave.ai/) is an AI-powered semantic search platform that helps you discover and retrieve knowledge across all your synced data sources. Built for modern teams, Airweave enables fast, relevant search results using neural, hybrid, or keyword-based strategies tailored to your needs.
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With Airweave, you can:
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-**Search smarter**: Use natural language queries to uncover information stored across your connected tools and databases
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-**Unify your data**: Seamlessly access content from sources like code, docs, chat, emails, cloud files, and more
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-**Customize retrieval**: Select between hybrid (semantic + keyword), neural, or keyword search strategies for optimal results
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-**Boost recall**: Expand search queries with AI to find more comprehensive answers
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-**Rerank results using AI**: Prioritize the most relevant answers with powerful language models
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-**Get instant answers**: Generate clear, AI-powered responses synthesized from your data
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In Sim, the Airweave integration empowers your agents to search, summarize, and extract insights from all your organization’s data via a single tool. Use Airweave to drive rich, contextual knowledge retrieval within your workflows—whether answering questions, generating summaries, or supporting dynamic decision-making.
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{/* MANUAL-CONTENT-END */}
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## Usage Instructions
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Search across your synced data sources using Airweave. Supports semantic search with hybrid, neural, or keyword retrieval strategies. Optionally generate AI-powered answers from search results.
Copy file name to clipboardExpand all lines: apps/sim/app/workspace/[workspaceId]/w/[workflowId]/components/panel/components/editor/components/sub-block/components/skill-input/skill-input.tsx
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