Instructions for AI coding agents working in the .NET codebase. See ./.github/skills/build-and-test/SKILL.md for detailed instructions on building, testing, and linting projects. See ./.github/skills/project-structure/SKILL.md for an overview of the project structure. See ./.github/skills/pull-requests/SKILL.md for guidance on writing PR descriptions and handling/resolving PR review comments. The framework integrates with Microsoft.Extensions.AI and Microsoft.Extensions.AI.Abstractions (external NuGet packages) using types like IChatClient, FunctionInvokingChatClient, AITool, AIFunction, ChatMessage, and AIContent. When developing or reviewing code, verify adherence to these key design principles: Samples (in ./samples/ folder) should…
Guidance for creating pull requests and handling PR review comments in the Agent Framework repository. Use this when writing a PR description (filling out the PR template) or when responding to and resolving review comments on an existing PR.
How to build, run and verify the .NET sample projects in the Agent Framework repository. Use this when a user wants to verify that the samples still function as expected.
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. 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: Then run verify-samples: The tool itself needs: - AZUREOPENAIENDPOINT — for the AI verification agent - AZUREOPENAIDEPLOYMENT_NAME (optional, defaults to gpt-5-mini) Individual samples require their own env vars (e.g., AZUREAIPROJECT_ENDPOINT). The tool automatically checks and…
Score how concentrated and risky a portfolio is on a 0-100 scale from its position weights. Use when the user asks how risky their portfolio is, whether it is too concentrated, or for a diversification check.
Estimate whether a stock looks cheap or expensive using a price-to-earnings (P/E) based fair-value method. Use when the user asks if a stock is over- or under-valued, or for a fair-value / target price.
When the user asks about portfolio risk or concentration: 1. Read references/risk-bands.md to understand the score bands and what drives them. 2. Compute each holding's market value (shares × price) — use the getstockprice tool for current prices if you do not already have them. 3. Run scripts/risk_score.py with one --position VALUE argument per holding, e.g. --position 18518 --position 17201 --position 16177. 4. Report the 0-100 score, the band it falls in, and the largest single-position weight, then suggest (in…
When the user asks whether a stock is fairly valued, over-valued, or under-valued: 1. Read references/valuation-guide.md to pick a sensible target P/E for the company's sector. 2. Run scripts/valuation_metrics.py with the current price, trailing EPS, and the target P/E, e.g. --price 462.97 --eps 11.80 --target-pe 32. 3. Report the computed P/E, the fair-value estimate, and the percentage upside/downside, then state plainly whether the stock looks cheap or expensive on this measure. Always remind the user that a single P/E heuristic…
This file documents the structure and conventions of the .NET samples so that agents (AI or human) can maintain them without rediscovering decisions. 1. Progressive complexity: Sections 01→05 build from "hello world" to production. Within 01-get-started, projects are numbered 01–05 and each step adds exactly one concept.
Microsoft Agent Framework - a multi-language framework for building, orchestrating, and deploying AI agents. ADRs in docs/decisions/ capture significant design decisions and their rationale. They document considered alternatives, trade-offs, and the reasoning behind choices. Templates: - adr-template.md - Full template with detailed sections - adr-short-template.md - Abbreviated template for simpler decisions When proposing architectural changes, create an ADR to capture options considered and the decision rationale. See docs/decisions/README.md for the full process.
Guidance for creating pull requests and handling PR review comments in the Agent Framework repository. Use this when writing a PR description (filling out the PR template) or when responding to and resolving review comments on an existing PR.
Instructions for AI coding agents working in the Python codebase. Key Documentation: - DEVSETUP.md - Development environment setup and available poe tasks - CODINGSTANDARD.md - Coding standards, docstring format, and performance guidelines - samples/SAMPLE_GUIDELINES.md - Sample structure and guidelines - Python function-calling loop specification - Required behavior, scenario-to-test mapping, coverage gaps, and extra validation for function-loop changes Agent Skills (.github/skills/) — detailed, task-specific instructions loaded on demand: - python-development — coding standards, type annotations, docstrings, logging, performance - python-testing —…
Plain text files in a repository that tell a coding agent how the project works: commands to run, conventions to follow and things to avoid. CLAUDE.md, AGENTS.md, cursor rules and skills are the common kinds.
CLAUDE.md or AGENTS.md?
CLAUDE.md is read by Claude Code. AGENTS.md is an open format that Codex, Cursor and other agents read. Many projects keep one and point the other at it.
What is a skill?
A folder with a SKILL.md that describes one capability, such as filling PDFs or reviewing code. The agent loads it only when the task calls for it.
Can I search my own team's files too?
Your agents already can, over MCP, limited to the files you're allowed to read. Searching them from this page is coming.
MicrosoftSkill