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Copy file name to clipboardExpand all lines: .github/copilot-instructions.md
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@@ -46,6 +46,15 @@ When NOT running under CCA, guidance for creating commits and pushing changes:
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- Never push to an active PR without being explicitly asked, even in autopilot/yolo mode. Always wait for explicit instruction to push.
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- Never chain commit and push in the same command. Always commit first, report what was committed, then wait for an explicit push instruction. This creates a mandatory decision point.
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- Prefer creating a new commit rather than amending an existing one. Exceptions: (1) explicitly asked to amend, or (2) the existing commit is obviously broken with something minor (e.g., typo or comment fix) and hasn't been pushed yet.
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-**Before posting to GitHub (PRs, issues, comments):** Include the AI-generated content disclosure (see below).
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## AI-Generated Content Disclosure
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When posting any content to GitHub under a user's credentials — opening PRs, creating issues, commenting on PRs or issues, posting review comments, or any other public-facing action — and the account is **not** a dedicated "copilot" or "bot" account/app, you **MUST** include a concise, visible note (e.g. a `> [!NOTE]` alert) indicating the content was AI/Copilot-generated.
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This applies to all GitHub interactions: PR descriptions, issue bodies, comments, review comments, etc. Exceptions:
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- The account is a recognized bot or Copilot app account (e.g., `github-actions[bot]`, `copilot`), where the AI origin is already apparent from the account identity.
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- The user explicitly asks you to omit the disclosure.
Copy file name to clipboardExpand all lines: .github/skills/api-proposal/SKILL.md
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@@ -270,12 +270,7 @@ Present the complete draft to the user for review. Iterate based on feedback bef
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### Phase 5: Publish
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> **Agent disclaimer:** When publishing to GitHub on behalf of a user account, prepend the following disclaimer to the proposal body:
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>
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> ```markdown
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> > [!NOTE]
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> > This proposal was drafted with the help of an AI agent. Please review for accuracy and remove this notice once you're satisfied with the content.
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> ```
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> **AI-generated content disclosure:** When posting any content to GitHub (issue body, PR body, comments) under a user's credentials — i.e., the account is **not** a dedicated "copilot" or "bot" account/app — prepend a concise, visible note (e.g. a `> [!NOTE]` alert) indicating the content was AI/Copilot-generated. This applies to the initial proposal, iteration updates, and any follow-up comments posted on the user's behalf. Skip this if the user explicitly asks you to omit it.
Copy file name to clipboardExpand all lines: .github/skills/ci-analysis/SKILL.md
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@@ -9,6 +9,8 @@ Analyze CI build status and test failures in Azure DevOps and Helix for dotnet r
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> 🚨 **NEVER** use `gh pr review --approve` or `--request-changes`. Only `--comment` is allowed. Approval and blocking are human-only actions.
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> 📝 **AI-generated content disclosure:** When posting any content to GitHub (PR comments, retry commands, analysis summaries) under a user's credentials — i.e., the account is **not** a dedicated "copilot" or "bot" account/app — you **MUST** include a concise, visible note (e.g. a `> [!NOTE]` alert) indicating the content was AI/Copilot-generated. Skip this if the user explicitly asks you to omit it.
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**Workflow**: Gather PR context (Step 0) → run the script → read the human-readable output + `[CI_ANALYSIS_SUMMARY]` JSON → synthesize recommendations yourself. The script collects data; you generate the advice. For supplementary investigation beyond the script, MCP tools (AzDO, Helix, GitHub) provide structured access when available; the script and `gh` CLI work independently when they're not.
Copy file name to clipboardExpand all lines: .github/skills/code-review/SKILL.md
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When presenting the final review (whether as a PR comment or as output to the user), use the following structure. This ensures consistency across reviews and makes the output easy to scan.
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> 📝 **AI-generated content disclosure:** When posting review content to GitHub (PR review comments, PR comments) under a user's credentials — i.e., the account is **not** a dedicated "copilot" or "bot" account/app — you **MUST** include a concise, visible note (e.g. a `> [!NOTE]` alert) indicating the content was AI/Copilot-generated. Skip this if the user explicitly asks you to omit it.
Copy file name to clipboardExpand all lines: .github/skills/performance-benchmark/SKILL.md
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Post a comment on the PR to trigger EgorBot with your benchmark. The general format is:
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> 📝 **AI-generated content disclosure:** When posting benchmark comments to GitHub under a user's credentials — i.e., the account is **not** a dedicated "copilot" or "bot" account/app — you **MUST** include a concise, visible note (e.g. a `> [!NOTE]` alert) indicating the content was AI/Copilot-generated. Skip this if the user explicitly asks you to omit it.
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@EgorBot[targets][options][BenchmarkDotNet args]
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```cs
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// Your benchmark code here
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```
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> **Note:** The @EgorBot command must not be inside the code block. Only the benchmark code should be inside the code block.
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> **Note:** When using @EgorBot, follow these formatting rules:
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> - The @EgorBot command must not be inside the code block.
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> - Only the benchmark code should be inside the code block.
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> - Do not place any additional text between the @EgorBot command line and the code block, as EgorBot will treat it as additional command arguments.
Copy file name to clipboardExpand all lines: .github/skills/vmr-codeflow-status/SKILL.md
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> 🚨 **NEVER** use `gh pr review --approve` or `--request-changes`. Only `--comment` is allowed. Approval and blocking are human-only actions.
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> 📝 **AI-generated content disclosure:** When posting any content to GitHub (PR comments, analysis summaries) under a user's credentials — i.e., the account is **not** a dedicated "copilot" or "bot" account/app — you **MUST** include a concise, visible note (e.g. a `> [!NOTE]` alert) indicating the content was AI/Copilot-generated. Skip this if the user explicitly asks you to omit it.
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**Workflow**: Run the script → read the human-readable output + `[CODEFLOW_SUMMARY]` JSON → synthesize recommendations yourself. The script collects data; you generate the advice.
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