<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Spec on AI Knowledge Base</title><link>https://learn-ai.blindshot.kz/content_type/spec/</link><description>Recent content in Spec on AI Knowledge Base</description><generator>Hugo</generator><language>en-us</language><atom:link href="https://learn-ai.blindshot.kz/content_type/spec/index.xml" rel="self" type="application/rss+xml"/><item><title>Symphony Service Specification</title><link>https://learn-ai.blindshot.kz/docs/openai/symphony/spec/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/openai/symphony/spec/</guid><description>Complete technical specification for implementing Symphony: six architectural layers, orchestration state machine, workspace management, agent runner protocol, polling and scheduling, retry semantics, and observability.</description></item><item><title>Advanced setup</title><link>https://learn-ai.blindshot.kz/docs/anthropic/claude-code/setup/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/claude-code/setup/</guid><description>System requirements, platform-specific installation, version management, and uninstallation for Claude Code.</description></item><item><title>Agent Specs</title><link>https://learn-ai.blindshot.kz/docs/pydantic-ai/agent-spec/_overview/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/pydantic-ai/agent-spec/_overview/</guid><description/></item><item><title>An Overview of Cohere's Models</title><link>https://learn-ai.blindshot.kz/docs/cohere/docs/models/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/cohere/docs/models/</guid><description>Cohere has a variety of models that cover many different use cases. If you need more customization, you can train a model to tune it to your specific use case.</description></item><item><title>Application-specific evaluation approaches</title><link>https://learn-ai.blindshot.kz/docs/langchain/langsmith/evaluation-approaches/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/langchain/langsmith/evaluation-approaches/</guid><description/></item><item><title>Architecture</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/architecture/_overview/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/architecture/_overview/</guid><description/></item><item><title>Aspect Critique</title><link>https://learn-ai.blindshot.kz/docs/ragas/concepts/metrics/available_metrics/aspect_critic/_overview/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/ragas/concepts/metrics/available_metrics/aspect_critic/_overview/</guid><description/></item><item><title>Authorization</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/basic/authorization/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/basic/authorization/</guid><description>&lt;p&gt;The MCP authorization specification defines the OAuth 2.0-based flow that remote MCP servers use to authenticate clients, and it is the formal basis for everything the higher-level registry authentication guide simplifies. Focus on the required OAuth grant types, token scoping rules, and the metadata discovery mechanism that clients use to find a server&amp;rsquo;s authorization endpoint. A key gotcha is that the spec mandates specific OAuth metadata fields that many generic OAuth libraries do not populate by default, so you may need custom configuration even when using well-known auth frameworks. This is dense specification text best read alongside a working implementation for reference.&lt;/p&gt;</description></item><item><title>Backends</title><link>https://learn-ai.blindshot.kz/docs/langchain/oss/javascript/deepagents/backends/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/langchain/oss/javascript/deepagents/backends/</guid><description>Choose and configure filesystem backends for deep agents. You can specify routes to different backends, implement virtual filesystems, and enforce policies.</description></item><item><title>Backends</title><link>https://learn-ai.blindshot.kz/docs/langchain/oss/python/deepagents/backends/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/langchain/oss/python/deepagents/backends/</guid><description>Choose and configure filesystem backends for deep agents. You can specify routes to different backends, implement virtual filesystems, and enforce policies.</description></item><item><title>Browse Collections</title><link>https://learn-ai.blindshot.kz/docs/chroma/docs/cli/browse/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/chroma/docs/cli/browse/</guid><description>Inspect your Chroma collections with an in-terminal UI.</description></item><item><title>Cancellation</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/basic/utilities/cancellation/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/basic/utilities/cancellation/</guid><description/></item><item><title>Completion</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/server/utilities/completion/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/server/utilities/completion/</guid><description/></item><item><title>Count Assistants</title><link>https://learn-ai.blindshot.kz/docs/langchain/langsmith/agent-server-api/assistants/count-assistants/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/langchain/langsmith/agent-server-api/assistants/count-assistants/</guid><description>Get the count of assistants matching the specified criteria.</description></item><item><title>Count Crons</title><link>https://learn-ai.blindshot.kz/docs/langchain/langsmith/agent-server-api/crons/count-crons/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/langchain/langsmith/agent-server-api/crons/count-crons/</guid><description>Get the count of crons matching the specified criteria.</description></item><item><title>Count Threads</title><link>https://learn-ai.blindshot.kz/docs/langchain/langsmith/agent-server-api/threads/count-threads/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/langchain/langsmith/agent-server-api/threads/count-threads/</guid><description>Get the count of threads matching the specified criteria.</description></item><item><title>Crafting Effective Agents</title><link>https://learn-ai.blindshot.kz/docs/crewai/en/guides/agents/crafting-effective-agents/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/crewai/en/guides/agents/crafting-effective-agents/</guid><description>Learn best practices for designing powerful, specialized AI agents that collaborate effectively to solve complex problems.</description></item><item><title>Create custom subagents</title><link>https://learn-ai.blindshot.kz/docs/anthropic/claude-code/sub-agents/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/claude-code/sub-agents/</guid><description>Create and use specialized AI subagents in Claude Code for task-specific workflows and improved context management.</description></item><item><title>Customize Agents</title><link>https://learn-ai.blindshot.kz/docs/crewai/en/learn/customizing-agents/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/crewai/en/learn/customizing-agents/</guid><description>A comprehensive guide to tailoring agents for specific roles, tasks, and advanced customizations within the CrewAI framework.</description></item><item><title>Delete Model Checkpoints</title><link>https://learn-ai.blindshot.kz/docs/wandb/api-reference/models/delete-model-checkpoints/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/wandb/api-reference/models/delete-model-checkpoints/</guid><description>Delete specific checkpoints for a model.</description></item><item><title>deprecated-spec</title><link>https://learn-ai.blindshot.kz/docs/together-ai/deprecated-spec/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/together-ai/deprecated-spec/</guid><description/></item><item><title>Elicitation</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/client/elicitation/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/client/elicitation/</guid><description/></item><item><title>Evaluation</title><link>https://learn-ai.blindshot.kz/docs/mistral/docs/guides/evaluation/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/mistral/docs/guides/evaluation/</guid><description>Guide to evaluating LLMs for specific tasks with metrics, human, and LLM-based methods</description></item><item><title>EXA Search Web Loader</title><link>https://learn-ai.blindshot.kz/docs/crewai/en/tools/search-research/exasearchtool/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/crewai/en/tools/search-research/exasearchtool/</guid><description>The &amp;lsquo;EXASearchTool&amp;rsquo; is designed to perform a semantic search for a specified query from a text&amp;rsquo;s content across the internet.</description></item><item><title>Filtering with Where</title><link>https://learn-ai.blindshot.kz/docs/chroma/cloud/search-api/filtering/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/chroma/cloud/search-api/filtering/</guid><description>Learn how to filter search results using Where expressions and the Key/K class to narrow down your search to specific documents, IDs, or metadata values.</description></item><item><title>Fireworks Agent: Supervised Fine-Tuning</title><link>https://learn-ai.blindshot.kz/docs/fireworks-ai/fine-tuning/agent/sft/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/fireworks-ai/fine-tuning/agent/sft/</guid><description>Run end-to-end SFT with Fireworks Agent — dataset inspection, hyperparameter sweep, evaluator-guided selection, and a deployed winner.</description></item><item><title>Fork a run</title><link>https://learn-ai.blindshot.kz/docs/wandb/models/runs/forking/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/wandb/models/runs/forking/</guid><description>Explore different parameters or models from a specific point in an experiment without impacting the original run.</description></item><item><title>Generate dense embeddings</title><link>https://learn-ai.blindshot.kz/docs/chroma/reference/embeddings-api/generate-dense-embeddings/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/chroma/reference/embeddings-api/generate-dense-embeddings/</guid><description>Generate dense vector embeddings for the given texts using the specified model. Provide either &amp;lsquo;instructions&amp;rsquo; or both &amp;rsquo;task&amp;rsquo; and &amp;rsquo;target&amp;rsquo; alongside &amp;rsquo;texts&amp;rsquo;.</description></item><item><title>Generate sparse embeddings</title><link>https://learn-ai.blindshot.kz/docs/chroma/reference/embeddings-api/generate-sparse-embeddings/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/chroma/reference/embeddings-api/generate-sparse-embeddings/</guid><description>Generate sparse vector embeddings for the given texts using the specified model. Provide either &amp;lsquo;instructions&amp;rsquo; or both &amp;rsquo;task&amp;rsquo; and &amp;rsquo;target&amp;rsquo; alongside &amp;rsquo;texts&amp;rsquo;. Set &amp;lsquo;fetch_labels&amp;rsquo; to true to include token labels in the response.</description></item><item><title>Generative UI</title><link>https://learn-ai.blindshot.kz/docs/ag-ui/concepts/generative-ui-specs/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/ag-ui/concepts/generative-ui-specs/</guid><description>Understanding AG-UI&amp;rsquo;s relationship with generative UI specifications</description></item><item><title>Get Thread State At Checkpoint</title><link>https://learn-ai.blindshot.kz/docs/langchain/langsmith/agent-server-api/threads/get-thread-state-at-checkpoint-1/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/langchain/langsmith/agent-server-api/threads/get-thread-state-at-checkpoint-1/</guid><description>Get state for a thread at a specific checkpoint.</description></item><item><title>Get Thread State At Checkpoint</title><link>https://learn-ai.blindshot.kz/docs/langchain/langsmith/agent-server-api/threads/get-thread-state-at-checkpoint/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/langchain/langsmith/agent-server-api/threads/get-thread-state-at-checkpoint/</guid><description>Get state for a thread at a specific checkpoint.</description></item><item><title>Groq</title><link>https://learn-ai.blindshot.kz/docs/wandb/weave/guides/integrations/groq/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/wandb/weave/guides/integrations/groq/</guid><description>Track and monitor Groq&amp;rsquo;s ultra-fast LPU™ inference with Weave, capturing model calls, performance metrics, and function chains for high-speed LLM applications using Groq&amp;rsquo;s specialized hardware acceleration.</description></item><item><title>Index creation error - missing spec parameter</title><link>https://learn-ai.blindshot.kz/docs/pinecone/troubleshooting/index-creation-error-missing-spec/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/pinecone/troubleshooting/index-creation-error-missing-spec/</guid><description/></item><item><title>Key Changes</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/changelog/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/changelog/</guid><description/></item><item><title>Ledger &amp; Debugging for RL Rollouts</title><link>https://learn-ai.blindshot.kz/docs/fireworks-ai/fine-tuning/rl-rollout-debugging/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/fireworks-ai/fine-tuning/rl-rollout-debugging/</guid><description>Inspect snapshot history, reset the ledger, and understand how in-flight requests behave during a weight swap.</description></item><item><title>Lifecycle</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/basic/lifecycle/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/basic/lifecycle/</guid><description>&lt;p&gt;The lifecycle specification defines the three phases every MCP connection goes through: initialization, operation, and shutdown. Focus especially on the initialization handshake where client and server exchange capabilities &amp;ndash; getting this wrong is the most common source of connection failures. Note that the protocol version negotiation happens here too, so mismatched versions between client and server will fail fast at this stage rather than producing mysterious errors later.&lt;/p&gt;</description></item><item><title>LLM gateway configuration</title><link>https://learn-ai.blindshot.kz/docs/anthropic/claude-code/llm-gateway/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/claude-code/llm-gateway/</guid><description>Learn how to configure Claude Code to work with LLM gateway solutions. Covers gateway requirements, authentication configuration, model selection, and provider-specific endpoint setup.</description></item><item><title>Log traces to a specific project</title><link>https://learn-ai.blindshot.kz/docs/langchain/langsmith/log-traces-to-project/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/langchain/langsmith/log-traces-to-project/</guid><description/></item><item><title>Logging</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/server/utilities/logging/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/server/utilities/logging/</guid><description/></item><item><title>MCP Get</title><link>https://learn-ai.blindshot.kz/docs/langchain/langsmith/agent-server-api/mcp/mcp-get/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/langchain/langsmith/agent-server-api/mcp/mcp-get/</guid><description>Implemented according to the Streamable HTTP Transport specification.</description></item><item><title>MCP Inspector</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/docs/tools/inspector/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/docs/tools/inspector/</guid><description>In-depth guide to using the MCP Inspector for testing and debugging Model Context Protocol servers</description></item><item><title>MCP Post</title><link>https://learn-ai.blindshot.kz/docs/langchain/langsmith/agent-server-api/mcp/mcp-post/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/langchain/langsmith/agent-server-api/mcp/mcp-post/</guid><description>Implemented according to the Streamable HTTP Transport specification.</description></item><item><title>Multi-agent patterns</title><link>https://learn-ai.blindshot.kz/docs/openai/agents-sdk/multi_agent/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/openai/agents-sdk/multi_agent/</guid><description>Architect teams of agents that collaborate, escalate, or specialize by capability.</description></item><item><title>Multimodal Inputs</title><link>https://learn-ai.blindshot.kz/docs/ag-ui/sdk/js/core/multimodal-inputs/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/ag-ui/sdk/js/core/multimodal-inputs/</guid><description>Use modality-specific user input parts with typed data/url sources in @ag-ui/core</description></item><item><title>Multimodal Inputs</title><link>https://learn-ai.blindshot.kz/docs/ag-ui/sdk/python/core/multimodal-inputs/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/ag-ui/sdk/python/core/multimodal-inputs/</guid><description>Use modality-specific user input parts with typed data/url sources in ag_ui.core</description></item><item><title>Overview</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/basic/_overview/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/basic/_overview/</guid><description/></item><item><title>Overview</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/server/_overview/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/server/_overview/</guid><description/></item><item><title>Oxylabs Scrapers</title><link>https://learn-ai.blindshot.kz/docs/crewai/en/tools/web-scraping/oxylabsscraperstool/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/crewai/en/tools/web-scraping/oxylabsscraperstool/</guid><description>Oxylabs Scrapers allow to easily access the information from the respective sources. Please see the list of available sources below:</description></item><item><title>Pagination</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/server/utilities/pagination/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/server/utilities/pagination/</guid><description/></item><item><title>PDF Text Writing Tool</title><link>https://learn-ai.blindshot.kz/docs/crewai/en/tools/file-document/pdf-text-writing-tool/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/crewai/en/tools/file-document/pdf-text-writing-tool/</guid><description>The &amp;lsquo;PDFTextWritingTool&amp;rsquo; writes text to specific positions in a PDF, supporting custom fonts.</description></item><item><title>Ping</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/basic/utilities/ping/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/basic/utilities/ping/</guid><description/></item><item><title>Plugins reference</title><link>https://learn-ai.blindshot.kz/docs/anthropic/claude-code/plugins-reference/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/claude-code/plugins-reference/</guid><description>Complete technical reference for Claude Code plugin system, including schemas, CLI commands, and component specifications.</description></item><item><title>Progress</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/basic/utilities/progress/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/basic/utilities/progress/</guid><description/></item><item><title>Prompts</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/server/prompts/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/server/prompts/</guid><description>&lt;p&gt;Prompts are the least commonly used of the three MCP primitives, but they fill an important niche: reusable, parameterized templates that help users invoke common workflows. Think of them as saved recipes that combine a specific prompt structure with dynamic arguments. Unlike tools and resources, prompts are user-initiated &amp;ndash; the user explicitly selects a prompt from a menu rather than the model discovering it automatically. This makes them ideal for standardizing repetitive interactions like &amp;ldquo;summarize this codebase&amp;rdquo; or &amp;ldquo;review this PR.&amp;rdquo;&lt;/p&gt;</description></item><item><title>Query threads using the SDK</title><link>https://learn-ai.blindshot.kz/docs/langchain/langsmith/query-threads/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/langchain/langsmith/query-threads/</guid><description>Programmatically fetch and inspect multi-turn conversation threads from your LangSmith projects.</description></item><item><title>Rate limits</title><link>https://learn-ai.blindshot.kz/docs/openai/api/api/docs/guides/rate-limits/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/openai/api/api/docs/guides/rate-limits/</guid><description>Rate limits are restrictions that our API imposes on the number of times a user or client can access our services within a specified period of time.</description></item><item><title>REPL</title><link>https://learn-ai.blindshot.kz/docs/openai/agents-sdk/repl/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/openai/agents-sdk/repl/</guid><description>Use the interactive runner to prototype agents and inspect execution step by step.</description></item><item><title>Resources</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/server/resources/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/server/resources/</guid><description>&lt;p&gt;Resources are how MCP servers expose data to the model without requiring the model to &amp;ldquo;call&amp;rdquo; anything &amp;ndash; think of them as files or documents the application can pull into context. The key distinction from tools is that resources are application-controlled (the host decides when to read them), while tools are model-controlled (the model decides when to invoke them). Pay attention to the URI-based addressing scheme, which lets clients discover and subscribe to resource updates. If your use case is primarily about providing context rather than performing actions, resources are usually the better primitive.&lt;/p&gt;</description></item><item><title>Results</title><link>https://learn-ai.blindshot.kz/docs/openai/agents-sdk/results/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/openai/agents-sdk/results/</guid><description>Inspect agent outputs, tool calls, follow-up actions, and metadata returned by the runner.</description></item><item><title>Roots</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/client/roots/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/client/roots/</guid><description/></item><item><title>Sampling</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/client/sampling/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/client/sampling/</guid><description>&lt;p&gt;Sampling is the mechanism that allows an MCP server to request LLM completions through the client, effectively enabling servers to leverage AI capabilities without embedding their own model access. This is one of the most powerful and least intuitive parts of the MCP specification because it inverts the typical client-server relationship. Pay careful attention to the human-in-the-loop requirements, since the spec mandates that clients must obtain user approval before fulfilling sampling requests, which has significant UX implications. If you are building agentic MCP servers that need to reason or generate text, understanding this capability is essential.&lt;/p&gt;</description></item><item><title>Schema Reference</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/schema/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/schema/</guid><description/></item><item><title>Scrape Element From Website Tool</title><link>https://learn-ai.blindshot.kz/docs/crewai/en/tools/web-scraping/scrapeelementfromwebsitetool/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/crewai/en/tools/web-scraping/scrapeelementfromwebsitetool/</guid><description>The &amp;lsquo;ScrapeElementFromWebsiteTool&amp;rsquo; enables CrewAI agents to extract specific elements from websites using CSS selectors.</description></item><item><title>Scrape Website</title><link>https://learn-ai.blindshot.kz/docs/crewai/en/tools/web-scraping/scrapewebsitetool/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/crewai/en/tools/web-scraping/scrapewebsitetool/</guid><description>The &amp;lsquo;ScrapeWebsiteTool&amp;rsquo; is designed to extract and read the content of a specified website.</description></item><item><title>Search runs</title><link>https://learn-ai.blindshot.kz/docs/wandb/models/runs/search-runs/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/wandb/models/runs/search-runs/</guid><description>Learn how to search for specific runs by name or ID in your project&amp;rsquo;s Runs table or Workspace.</description></item><item><title>Selenium Scraper</title><link>https://learn-ai.blindshot.kz/docs/crewai/en/tools/web-scraping/seleniumscrapingtool/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/crewai/en/tools/web-scraping/seleniumscrapingtool/</guid><description>The &amp;lsquo;SeleniumScrapingTool&amp;rsquo; is designed to extract and read the content of a specified website using Selenium.</description></item><item><title>SEP Guidelines</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/community/sep-guidelines/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/community/sep-guidelines/</guid><description>Specification Enhancement Proposal (SEP) guidelines for proposing changes to the Model Context Protocol</description></item><item><title>SEP-986: Specify Format for Tool Names</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/community/seps/986-specify-format-for-tool-names/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/community/seps/986-specify-format-for-tool-names/</guid><description>Specify Format for Tool Names</description></item><item><title>SEP-986: Specify Format for Tool Names</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/seps/986-specify-format-for-tool-names/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/seps/986-specify-format-for-tool-names/</guid><description>Specify Format for Tool Names</description></item><item><title>Skills</title><link>https://learn-ai.blindshot.kz/docs/langchain/langsmith/fleet/skills/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/langchain/langsmith/fleet/skills/</guid><description>Use skills to give your agents access to specific capabilities.</description></item><item><title>Specification</title><link>https://learn-ai.blindshot.kz/docs/a2a/google/a2a/tree/main/specification/json/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/a2a/google/a2a/tree/main/specification/json/</guid><description>Complete A2A protocol specifications</description></item><item><title>Specification</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/_overview/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/_overview/</guid><description/></item><item><title>Specification Enhancement Proposals (SEPs)</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/community/seps/_overview/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/community/seps/_overview/</guid><description>Index of all MCP Specification Enhancement Proposals</description></item><item><title>Specification Enhancement Proposals (SEPs)</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/seps/_overview/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/seps/_overview/</guid><description>Index of all MCP Specification Enhancement Proposals</description></item><item><title>Specify a custom run ID</title><link>https://learn-ai.blindshot.kz/docs/langchain/langsmith/custom-run-id/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/langchain/langsmith/custom-run-id/</guid><description>How to specify a custom run ID when tracing with LangSmith.</description></item><item><title>Speculative Decoding</title><link>https://learn-ai.blindshot.kz/docs/fireworks-ai/deployments/speculative-decoding/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/fireworks-ai/deployments/speculative-decoding/</guid><description>Speed up generation with draft models and n-gram speculation</description></item><item><title>Spider Scraper</title><link>https://learn-ai.blindshot.kz/docs/crewai/en/tools/web-scraping/spidertool/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/crewai/en/tools/web-scraping/spidertool/</guid><description>The &amp;lsquo;SpiderTool&amp;rsquo; is designed to extract and read the content of a specified website using Spider.</description></item><item><title>Structured model outputs</title><link>https://learn-ai.blindshot.kz/docs/openai/api/api/docs/guides/structured-outputs/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/openai/api/api/docs/guides/structured-outputs/</guid><description>Understand how to ensure model responses follow specific JSON Schema you define.</description></item><item><title>Subagent streaming</title><link>https://learn-ai.blindshot.kz/docs/langchain/oss/javascript/deepagents/frontend/subagent-streaming/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/langchain/oss/javascript/deepagents/frontend/subagent-streaming/</guid><description>Display specialist subagents with streaming content, progress tracking, and collapsible cards</description></item><item><title>Subagent streaming</title><link>https://learn-ai.blindshot.kz/docs/langchain/oss/python/deepagents/frontend/subagent-streaming/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/langchain/oss/python/deepagents/frontend/subagent-streaming/</guid><description>Display specialist subagents with streaming content, progress tracking, and collapsible cards</description></item><item><title>Tasks</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/basic/utilities/tasks/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/basic/utilities/tasks/</guid><description/></item><item><title>Terminate Session</title><link>https://learn-ai.blindshot.kz/docs/langchain/langsmith/agent-server-api/mcp/terminate-session/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/langchain/langsmith/agent-server-api/mcp/terminate-session/</guid><description>Implemented according to the Streamable HTTP Transport specification.</description></item><item><title>Text &amp; Vision Fine-tuning</title><link>https://learn-ai.blindshot.kz/docs/mistral/docs/capabilities/finetuning/text-vision-finetuning/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/mistral/docs/capabilities/finetuning/text-vision-finetuning/</guid><description>Fine-tune Mistral&amp;rsquo;s text and vision models with custom datasets in JSONL format for domain-specific or conversational improvements</description></item><item><title>Time travel</title><link>https://learn-ai.blindshot.kz/docs/langchain/oss/javascript/langchain/frontend/time-travel/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/langchain/oss/javascript/langchain/frontend/time-travel/</guid><description>Inspect, navigate, and resume from any checkpoint in the conversation history</description></item><item><title>Time travel</title><link>https://learn-ai.blindshot.kz/docs/langchain/oss/python/langchain/frontend/time-travel/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/langchain/oss/python/langchain/frontend/time-travel/</guid><description>Inspect, navigate, and resume from any checkpoint in the conversation history</description></item><item><title>Tools</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/server/tools/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/server/tools/</guid><description>&lt;p&gt;Tools are the most commonly used MCP primitive &amp;ndash; they let the model invoke server-side functions with structured inputs and receive results. Focus on the JSON Schema-based input validation, which is how the model knows what arguments a tool accepts. A critical detail is that tool calls are model-initiated but require human approval in most host implementations, so design your tool descriptions to be clear enough that users understand what they are approving. Keep tool names concise and descriptions precise, as the model relies heavily on them for deciding when and how to call each tool.&lt;/p&gt;</description></item><item><title>Transports</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/basic/transports/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/2025-11-25/basic/transports/</guid><description>&lt;p&gt;MCP defines two transport mechanisms: stdio (standard input/output) and HTTP with Server-Sent Events (SSE). For local development and CLI-based servers, stdio is simpler and the right default choice. HTTP+SSE is needed when the server runs remotely or must handle multiple clients. A common gotcha is that the Streamable HTTP transport replaced the older SSE-only transport in the 2025-11-25 spec revision, so be careful not to follow outdated examples that use the previous approach.&lt;/p&gt;</description></item><item><title>Triggers Overview</title><link>https://learn-ai.blindshot.kz/docs/crewai/en/enterprise/guides/automation-triggers/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/crewai/en/enterprise/guides/automation-triggers/</guid><description>Understand how CrewAI AMP triggers work, how to manage them, and where to find integration-specific playbooks</description></item><item><title>Versioning</title><link>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/versioning/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/anthropic/mcp/specification/versioning/</guid><description/></item><item><title>View a specific run in a project</title><link>https://learn-ai.blindshot.kz/docs/wandb/models/runs/view-logged-runs/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/wandb/models/runs/view-logged-runs/</guid><description>Learn how to view a specific logged run and its properties using the W&amp;amp;B App or the LEET terminal UI.</description></item><item><title>Websearch</title><link>https://learn-ai.blindshot.kz/docs/mistral/docs/agents/connectors/websearch/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://learn-ai.blindshot.kz/docs/mistral/docs/agents/connectors/websearch/</guid><description>Websearch enables models to browse the web for real-time, up-to-date information and access specific websites</description></item></channel></rss>