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.
npx agentmods add agents/managedcode/dotnet-skills/agent-pipelinegit clone --depth 1 https://github.com/managedcode/dotnet-skillsWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00017 | $0.03335 |
| Opus 5 | $0.00009 | $0.01667 |
| Sonnet 5 | $0.00003 | $0.00667 |
| Haiku 4.5 | $0.00002 | $0.00333 |
Grade A, and why
agent-pipeline 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 2d ago.
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.
How it starts
The opening of the file, as written. The whole thing — 399 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent pipeline architecture
Agents in Microsoft Agent Framework use a layered pipeline architecture to process requests. Understanding this architecture helps you customize agent behavior by adding middleware, context providers, or client-level modifications at the appropriate layer.
::: zone pivot="programming-language-csharp"
ChatClientAgent Pipeline
The ChatClientAgent builds a pipeline with three main layers:
- Agent middleware - Optional decorators that wrap the agent via
.Use()for logging, validation, or transformation - Context layer - Manages chat history (
ChatHistoryProvider) and injects additional context (AIContextProviders) - Chat client layer - The
IChatClientwith optional middleware decorators that handle LLM communication
When you call RunAsync(), your request flows through each layer in sequence.
::: zone-end
::: zone pivot="programming-language-python"
Agent Pipeline
The Agent class builds a pipeline through class composition with two main components:
Agent (outer component):
- Agent Middleware + Telemetry - the
AgentMiddlewareLayerandAgentTelemetryLayerclasses handle middleware invocation and OpenTelemetry instrumentation - RawAgent - Core agent logic that invokes context providers and collects provider-added middleware
- Context Providers - Unified
context_providerslist manages history, additional context, and per-run chat/function middleware
ChatClient (separate and interchangeable component):
- FunctionInvocation - Handles tool calling loop, invoking Function Middleware + Telemetry per tool call
- Chat Middleware + Telemetry - Optional middleware chain and instrumentation layers, including any chat middleware added by context providers, running per model call
- RawChatClient - Provider-specific implementation (Azure OpenAI, OpenAI, Anthropic, etc.) that communicates with the LLM
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.
- 2d ago First seen · 399 lines · 17 tokens per session scan A 8dab3050269a
agent-pipeline is an agent published in the GitHub repository managedcode/dotnet-skills (477 stars, last pushed 2d ago), licensed MIT. It adds 17 tokens to every session and 3,335 once invoked, about $0.0001 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.
Other agents, from other repositories
observability
Prometheus-metrikker, OpenTelemetry-tracing, Grafana-dashboards og varsling.
research-agent
Utforsker kodebaser, undersøker problemer og samler kontekst før implementering.
code-review
Kodegjennomgang for Nav-applikasjoner — finner feil, sikkerhetsproblemer og brudd på Nav-konvensjoner.
rust-agent
Idiomatisk Rust-utvikling med cargo, clippy, error handling, async/tokio, unsafe og testing.
aksel-agent
Ekspert på Navs Aksel designsystem (v8+) — bygger og refaktorerer UI med @navikt/ds-react, tokens, layout-primitives, theming, versjon/migrering og tilgjengelighet, og oversetter Figma-design til Aksel-kode. Drevet av aksel-builder-skillen og Aksel MCP som fasit.
MAF Migration Agent
Use when migrating a .NET codebase to Microsoft Agent Framework (MAF) 1.3.0. Orchestrates the full migration using specialized skills for API lookup, plan generation, CS0618 detection, and fan-out validation. Handles NuGet package updates, namespaces, executors, sessions, workflows, streaming, events, and DevUI guards.