microsoft/copilot-camp is a collection of hands-on workshops for extending Microsoft 365 Copilot and building custom engine agents. Developers use it to learn how to create declarative agents, connectors, MCP servers, multi-agent workflows, API integrations, and other Copilot extensions. The catalogue entries are skills and instructions for these development workflows.
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 skills add microsoft/copilot-camp --skill foundry-researchgit clone --depth 1 https://github.com/microsoft/copilot-campWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/microsoft/copilot-camp/foundry-research)<a href="https://agentmods.dev/skills/microsoft/copilot-camp/foundry-research"><img src="https://agentmods.dev/badge/skills/microsoft/copilot-camp/foundry-research/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/microsoft/copilot-camp/foundry-research"><img src="https://agentmods.dev/badge/skills/microsoft/copilot-camp/foundry-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00079 | $0.00914 |
| Opus 5.5 | $0.00032 | $0.00366 |
| Sonnet 5.5 | $0.00016 | $0.00183 |
| Haiku 4.5 | $0.00008 | $0.00091 |
Grade A, and why
foundry-research 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 1mo 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 — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Microsoft Foundry Research Skill
What This Skill Does
This skill helps you deep-dive into Microsoft Foundry documentation and capabilities by:
- Searching multiple topics across Microsoft Foundry documentation
- Collecting architecture guides, model documentation, and deployment patterns
- Organizing findings into clear sections (Overview, Architecture, Models, Deployment, Best Practices)
- Generating a comprehensive research summary with links and code samples
When to Use This Skill
Activate this skill when you need:
- Overview of Microsoft Foundry platform and components
- Understanding of available models and their capabilities
- Deployment and configuration guidance
- Best practices for building with Foundry
- Integration patterns with Azure services
- Code samples and quickstart guides
Workflow
Step 1: Topic Definition
Ask the user to clarify their specific Foundry interest:
- Foundry platform overview? (architecture, components)
- Specific model? (which model and its capabilities)
- Deployment scenario? (local, cloud, hybrid)
- Integration use case? (agents, workflows, content generation)
Step 2: Multi-Topic Research
Conduct multiple searches across the Microsoft Learn MCP Server:
- Search: "Microsoft Foundry platform overview architecture"
- Search: "Microsoft Foundry models and capabilities"
- Search: "Microsoft Foundry deployment options"
- Search: "Microsoft Foundry best practices"
- Search: Specific topic based on user interest (e.g., "Foundry agents", "Foundry fine-tuning")
Step 3: Information Organization
Compile findings into these sections:
## Microsoft Foundry Research Summary
### Overview
[Platform description, key components, use cases]
### Architecture
[System design, core components, integration points]
### Available Models
[Model list with capabilities, performance characteristics]
### Deployment Options
[Local development, cloud deployment, hybrid approaches]
### Best Practices
[Recommended patterns, performance optimization, security]
### Getting Started
[Quickstart guides, code examples, resources]
### Related Services
[Azure integration, complementary services]
### Additional Resources
[Links to official documentation and samples]
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.
- 1mo ago First seen · 129 lines · 79 tokens per session scan A 1adf30ef8d4e
foundry-research is a skill published in the GitHub repository microsoft/copilot-camp (671 stars, last pushed yesterday), licensed MIT. It adds 79 tokens to every session and 914 once invoked, about $0.0003 per session on Opus 5.5. 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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