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Add email-drafter skill: personalized email drafting with tone analysis via WorkIQ (#1182)

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* Add email-drafter skill: personalized email drafting with tone analysis via WorkIQ

* fix: use single-quoted YAML scalar for description frontmatter
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Onur Senturk
2026-03-27 00:24:47 +01:00
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@@ -116,6 +116,7 @@ See [CONTRIBUTING.md](../CONTRIBUTING.md#adding-skills) for guidelines on how to
| [doublecheck](../skills/doublecheck/SKILL.md) | Three-layer verification pipeline for AI output. Extracts verifiable claims, finds supporting or contradicting sources via web search, runs adversarial review for hallucination patterns, and produces a structured verification report with source links for human review. | `assets/verification-report-template.md` |
| [editorconfig](../skills/editorconfig/SKILL.md) | Generates a comprehensive and best-practice-oriented .editorconfig file based on project analysis and user preferences. | None |
| [ef-core](../skills/ef-core/SKILL.md) | Get best practices for Entity Framework Core | None |
| [email-drafter](../skills/email-drafter/SKILL.md) | Draft and review professional emails that match your personal writing style. Analyzes your sent emails for tone, greeting, structure, and sign-off patterns via WorkIQ, then generates context-aware drafts for any recipient. USE FOR: draft email, write email, compose email, reply email, follow-up email, analyze email tone, email style. | None |
| [entra-agent-user](../skills/entra-agent-user/SKILL.md) | Create Agent Users in Microsoft Entra ID from Agent Identities, enabling AI agents to act as digital workers with user identity capabilities in Microsoft 365 and Azure environments. | None |
| [eval-driven-dev](../skills/eval-driven-dev/SKILL.md) | Add instrumentation, build golden datasets, write eval-based tests, run them, root-cause failures, and iterate — Ensure your Python LLM application works correctly. Make sure to use this skill whenever a user is developing, testing, QA-ing, evaluating, or benchmarking a Python project that calls an LLM. Use for making sure an LLM application works correctly, catching regressions after prompt changes, fixing unexpected behavior, or validating output quality before shipping. | `references/pixie-api.md` |
| [excalidraw-diagram-generator](../skills/excalidraw-diagram-generator/SKILL.md) | Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw. | `references/element-types.md`<br />`references/excalidraw-schema.md`<br />`scripts/.gitignore`<br />`scripts/README.md`<br />`scripts/add-arrow.py`<br />`scripts/add-icon-to-diagram.py`<br />`scripts/split-excalidraw-library.py`<br />`templates` |