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 skills/microsoft/agent-framework/verify-samples-toolnpx skills add microsoft/agent-framework --skill verify-samples-toolgit clone --depth 1 https://github.com/microsoft/agent-frameworkWhat 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 | $0.00040 | $0.02123 |
| Opus 5 | $0.00020 | $0.01061 |
| Sonnet 5 | $0.00008 | $0.00425 |
| Haiku 4.5 | $0.00004 | $0.00212 |
Grade A, and why
verify-samples-tool 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.
How it starts
The opening of the file, as written. The whole thing — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
verify-samples Tool
The verify-samples project (dotnet/eng/verify-samples/) is an automated tool that runs sample projects and verifies their output using deterministic checks and AI-powered verification.
Running verify-samples
Important: By default, samples must be pre-built before running verify-samples. Build the solution first, or pass --build to build samples during the run:
cd dotnet
dotnet build agent-framework-dotnet.slnx -f net10.0
Then run verify-samples:
# Run all samples across all categories
dotnet run --project eng/verify-samples -- --log results.log --csv results.csv
# Run a specific category
dotnet run --project eng/verify-samples -- --category 02-agents --log results.log
# Run specific samples by name
dotnet run --project eng/verify-samples -- Agent_Step02_StructuredOutput Agent_Step09_AsFunctionTool
# Control parallelism (default 8)
dotnet run --project eng/verify-samples -- --parallel 8 --log results.log
# Build samples during run (skips the need for a prior build step)
# This may cause build conflicts as multiple samples are built in parallel, so use with caution
dotnet run --project eng/verify-samples -- --build --log results.log
# Combine options
dotnet run --project eng/verify-samples -- --category 03-workflows --parallel 4 --log results.log --csv results.csv --md results.md
Required Environment Variables
The tool itself needs:
AZURE_OPENAI_ENDPOINT— for the AI verification agentAZURE_OPENAI_DEPLOYMENT_NAME(optional, defaults togpt-5-mini)
Individual samples require their own env vars (e.g., AZURE_AI_PROJECT_ENDPOINT). The tool automatically checks and skips samples with missing env vars.
Output Files
--log results.log— detailed per-sample log with stdout/stderr, AI reasoning, and a summary--csv results.csv— tabular summary with Sample, ProjectPath, Status, FailedChecks, and Failures columns--md results.md— Markdown summary with results table and collapsible failure details (suitable for GitHub PR comments)
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.
- yesterday First seen · 228 lines · 40 tokens per session scan A dbec3e9727ff
verify-samples-tool is a skill published in the GitHub repository microsoft/agent-framework (13,222 stars, last pushed 2d ago), licensed MIT. It adds 40 tokens to every session and 2,123 once invoked, about $0.0002 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 skills, from other repositories
swarmclaw
AI agent runtime and multi-agent orchestration platform. Teaches agents how to use SwarmClaw's 6 primitive tools, persistent memory, dreaming, delegation, connectors, credentials, and the skill system. Use when an agent is running on SwarmClaw and needs to understand the platform's capabilities.
agent-collaboration
Use this skill when coordinating multiple AI agents. Covers multi-agent patterns, handoffs, and orchestration strategies.
crewai-multi-agent
Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies…
strands-review
Local preview of the strands-agents/devtools /strands review agent. Body is the upstream Task Reviewer SOP verbatim — do not paraphrase. Use when the user types /strands-review, asks for a "strands review" of a PR, or wants to anticipate what the remote /strands review GitHub Action will flag. Findings are close but…
docs-writer
Draft or rewrite Strands Agents documentation pages. Use when writing new doc pages, rewriting pages that failed audit, drafting sections for existing pages, or writing blog posts and release notes about Strands. Also triggers on "write a doc", "draft a page", "rewrite the quickstart", "add a tutorial for X"…
pr-writer
Generates pull request titles and descriptions. Use when the user asks to create, open, write, draft, or generate a PR, pull request, or merge request description.