Agent Skills: calendly-api-2-event-types
Sub-skill of calendly-api: 2. Event Types.
ID: vamseeachanta/workspace-hub/calendly-api-2-event-types
177
Install this agent skill to your local
Skill Files
The files that make up calendly-api-2-event-types.
More agent skills
- research-citation-check当用户明确要求"核查/优化综述 `{主题}_review.tex` 的正文引用"、"运行 research-citation-check",或要求使用旧名 check-review-alignment skill 时使用。通过宿主 AI 的语义理解逐条核查引用是否与文献内容吻合,只在发现致命性引用错误时对"包含引用的句子"做最小化改写,并优先复用 `research-literature-review` 的渲染脚本输出 PDF/Word,过渡期允许 fallback 到旧名 systematic-literature-review。核心原则:不为了改而改,无法确定是否为致命性错误时保留原样并在报告中警告。⚠️ 不适用:用户只是想生成系统综述正文(应使用 research-literature-review);用户只是想新增/核对 BibTeX 条目(应使用专门的 bib 管理流程)。
- hf-cloud-sagemaker-deployment-plannerPlan and coordinate the deployment of a model to Amazon SageMaker AI. Use this skill whenever the user wants to deploy, host, serve, or expose a model on SageMaker or AWS — including phrases like "deploy a model", "host this LLM on AWS", "serve this embedding model", "deploy a reranker", "deploy a text-to-image / diffusion model", "host this for async inference", "create an endpoint", "serve my fine-tuned model", or any request that involves making a model available for inference on AWS. Use this even when the user is vague (e.g. "I just want to get this running on AWS, you figure it out"). Works for text-generation LLMs, embedding models, rerankers, classifiers, text-to-image / diffusion models — picks the right serving stack and chooses between real-time and async inference. This is the entry-point skill for SageMaker deployment work — it asks clarifying questions, picks a deployment pathway, and coordinates the other deployment skills.
- axiom-audit-swiftui-navUse when the user mentions SwiftUI navigation issues, deep linking problems, state restoration bugs, or navigation architecture review.
- app_evaluatorA professional skill for App Evaluation (evaluating app's performance with score) and App Improvement (giving professional suggestions for improving the app's performance).
- remotion-interactivityStructure Remotion markup for interactivity
- n8n-code-toolWrite JavaScript or Python for the n8n Custom Code Tool (@n8n/n8n-nodes-langchain.toolCode) — the AI-agent-callable tool, NOT the workflow Code node. Use when building a Code Tool attached to an AI Agent, writing code that an LLM will invoke, parsing the `query` input, returning a string result, defining an input schema for structured arguments (specifyInputSchema, jsonSchemaExample, DynamicStructuredTool), or troubleshooting errors like \"Wrong output type returned\", \"No execution data available\", \"The response property should be a string, but it is an object\", \"Cannot assign to read only property 'name'\", or an AI agent that refuses to call the tool. Covers the critical differences between Code node and Code Tool: return format (string vs `[{json:{...}}]`), unavailability of `$fromAI`/`$input`/`$helpers` in the Code Tool sandbox, naming rules for AI invocation, and when to use `toolWorkflow`/HTTP Request Tool instead.