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docs-product-alignment

Audit and update docs/copilot/ documentation to accurately reflect current VS Code AI capabilities. Use when: competitive analysis reveals gaps, product launches new features, docs use outdated framing, or keyword coverage needs strengthening for discoverability by users and AI agents. Produces a gap analysis plus targeted edits across affected files.

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SKILL.md
Quality
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Documentation Product Alignment

Audit VS Code Copilot documentation against current product capabilities and produce targeted, style-compliant edits. Follow the docs-writing style guide for all writing rules.

Guardrails

  • Factual only. Every claim must map to something the product does today. No superlatives, no competitive comparisons, no invented terminology.
  • Two audiences. Humans read the prose; AI agents and search crawlers index Keywords, MetaDescriptions, and opening paragraphs. Both matter.
  • Minimal edits. Change only what is inaccurate, outdated, or missing. One precise sentence beats a rewritten section.
  • Verifiable. If you cannot point to a UI element, setting, or documented behavior, do not write it.

Workflow

  1. Gather context. Read the latest release notes, check github.com/features/copilot, and review any competitive claims or feature matrices the user provides.
  2. Audit high-traffic pages. Read each page and compare against current product truth. Focus on MetaDescriptions, Keywords, opening paragraphs, and terminology.
  3. Gap analysis. List what is inaccurate, outdated, or missing. Map each gap to a file and location. Prioritize by page traffic.
  4. Edit. Apply targeted changes. Vary phrasing across pages to avoid repetition.
  5. Verify. Search changed files for banned words, em-dashes, and MetaDescription length violations.

High-traffic pages to always check:

Terminology

Use these terms consistently. The "Avoid" column lists terms that creep in but should not.

ConceptUseAvoid
Autonomous coding sessionsagentsagent mode, agentic workflows
Running without user interactionbackground agentsbackground agent mode
Code suggestions as you typeinline suggestionscode completions, autocomplete
Predicted next edit locationnext edit suggestions (NES)predictive edits
Understanding code across filesworkspace context, cross-file reasoningdeep semantic understanding (overuse)
GitHub's search for code contextGitHub's code searchremote search
VS Code's type/symbol analysislanguage intelligence (IntelliSense, LSP)code intelligence
Multiple AI model optionsmultiple AI modelsleading AI models
Plan then implement workflowPlan agent, implementation agentplanning mode

Capability areas

When auditing, ensure docs accurately cover these areas:

  • Agents: plan, implement, verify, parallel sessions, local/background/cloud, third-party support
  • Context: semantic search, language intelligence (LSP), GitHub code search, cross-repo awareness
  • Multi-file editing: coordinated changes, architecture-level refactoring, framework migrations
  • Enterprise: organization policies, model access controls, content exclusions, trust boundaries
  • SDLC workflow: Plan agent, implementation agent, Copilot code review, background/cloud handoff
  • Scale: large codebases, monorepos, multi-root workspaces, remote indexing
Repository
microsoft/vscode-docs
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