semantic-kernel

A guide to using Semantic Kernel, a .NET toolkit for connecting AI services with prompts and C# functions. Plugins are groups of functions that an AI model can call.

In plain words
What is it for?
Use it to add AI prompts, plugins, function calling, orchestration, semantic search, or to review and update Semantic Kernel code.
Why use it?
It helps organize AI features so they can be tested, maintained, and connected to application services.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/managedcode/dotnet-skills/semantic-kernel
Any agent
npx skills add managedcode/dotnet-skills --skill semantic-kernel
Clone the repo
git clone --depth 1 https://github.com/managedcode/dotnet-skills

Made for: Claude Code, Codex.

Per session 116 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,330 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00116 $0.02330
Opus 5 $0.00058 $0.01165
Sonnet 5 $0.00023 $0.00466
Haiku 4.5 $0.00012 $0.00233

Measured yesterday against content hash 9b6da01afa5a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

semantic-kernel scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

catalog/Frameworks/Semantic-Kernel/skills/semantic-kernel/SKILL.md · 290 lines

How it starts

The opening of the file, as written. The whole thing — 290 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Semantic Kernel for .NET

Trigger On

  • adding AI-driven prompts, plugins, or orchestration to a .NET app
  • reviewing kernel construction, service registration, or plugin usage
  • building function-calling patterns with LLMs
  • migrating older Semantic Kernel code to current APIs

Documentation

References

  • patterns.md - Plugin patterns, function calling patterns, multi-agent patterns, prompt templates, and RAG patterns
  • anti-patterns.md - Common Semantic Kernel mistakes and how to avoid them

Core Concepts

Concept Description
Kernel Central orchestrator for AI services and plugins
Plugin Collection of functions exposed to the LLM
Function Native C# method or prompt template
Chat Completion LLM service for generating responses
Memory Vector storage for semantic search

Workflow

  1. Build the Kernel with required services
  2. Create Plugins with well-described functions
  3. Configure Function Calling for automatic tool use
  4. Handle Responses and manage conversation state
  5. Test and Observe AI behavior with logging
  6. For Semantic Kernel dotnet-1.79.0 and later, keep OpenAPI plugin server URL validation enabled, do not re-enable automatic redirects on the default HttpPlugin or WebFileDownloadPlugin clients without an explicit trusted-host policy, and use the current Microsoft Agent Framework-compatible migration samples when moving SK agent code to Agent Framework.
  7. Re-test Cosmos DB vector-store queries, file and document plugins, OpenAPI server-variable URLs, and Ollama reasoning settings after upgrading to 1.79.0. The release fixes the Cosmos vector-store path, rejects mixed-separator UNC paths, URL-encodes OpenAPI server variables, adds Ollama Think, and allows deterministic TimePlugin tests through TimeProvider injection.
  8. Treat the Prompty.Core 2.0.0-beta.3 update in 1.79.0 as a breaking dependency change. Re-run prompt-template tests and remove security workarounds that are no longer needed after the vulnerable transitive version is gone.
  9. In 1.80.0, re-test OpenAPI plugin HTTP-client defaults and Gemini calls that restrict FunctionChoiceBehavior to a supplied function list. The migrated .NET MEVD providers are no longer owned by Semantic Kernel; follow their redirect guidance and keep vector-provider package references explicit during upgrades.

Read the full file on GitHub · 290 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 290 lines · 116 tokens per session scan A 9b6da01afa5a

Subscribe to this mod's changes

semantic-kernel is a skill published in the GitHub repository managedcode/dotnet-skills (477 stars, last pushed 2d ago), licensed MIT. It adds 116 tokens to every session and 2,330 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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