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mcp/skillhub

Agent Skill

Code Tour skill

code-tourgithub/awesome-copilotskills/code-tour/SKILL.md

Use this skill to create CodeTour .tour files — persona-targeted, step-by-step walkthroughs that link to real files and line numbers. Trigger for: "create a tour", "make a code tour", "generate a tour", "onboarding tour", "tour for this PR", "tour for this bug", "RCA tour", "architecture tour", "explain how X works", "vibe check", "PR review tour", "contributor guide", "help someone ramp up", or any request for a structured walkthrough through code. Supports 20 developer personas (new joiner, bug fixer, architect, PR reviewer, vibecoder, security reviewer, and more), all CodeTour step types (file/line, selection, pattern, uri, commands, view), and tour-level fields (ref, isPrimary, nextTour). Works with any repository in any language.

40kMIT

always on

184 tokname + description

once used

5,375 tokSKILL.md body

bundled files

42 scripts

repo stars

40kGitHub

Install the Code Tour skill

Skills CLI (Claude Code, Codex, Cursor and others)

npx skills add https://github.com/github/awesome-copilot --skill code-tour

Claude Code, by hand (all projects)

git clone --depth 1 https://github.com/github/awesome-copilot.git /tmp/awesome-copilot
mkdir -p ~/.claude/skills
cp -R /tmp/awesome-copilot/skills/code-tour ~/.claude/skills/code-tour

For one project only, copy the folder into .claude/skills/ in that project instead. The agent picks it up when a task matches its description.

What it costs your context

Agent Skills load in three steps. Tokens counted with the o200k tokenizer; your model's count will differ a little.

WhenWhat loadsCost
Every sessionName and description184 tok
When the agent uses itThe SKILL.md instructions5,375 tok
Only if opened4 bundled files (36 KB)varies

Until it is used, code-tour costs about 7.4× less than the median MCP server we measured (1,362 tokens on every turn). Installing all 150 skills from github/awesome-copilot would load 9,863 tokens of descriptions. Skills vs MCP study

Checks

  • Ships scripts the agent can run. Read them before installing.
  • The instructions are over 5,000 tokens, the Agent Skills specification's guideline for SKILL.md.

Checked 2026-10-22 · method

What's inside

The headings of its SKILL.md. Read the full file on GitHub.

  • Code Tour Skill
  • Real-world .tour files on GitHub
  • Step 1: Discover the repo
  • Entry points by language/framework
  • Repo type variants — adjust focus accordingly
  • Large repo strategy
  • Step 2: Read the intent — infer everything you can, ask only what you can't
  • Intent map
  • PR tour recipe
  • User-provided customization — always honor these
  • Step 3: Read the actual files — no exceptions
  • Step 4: Write the tour
  • Tour root
  • Step types — full reference
  • When to use each step type
  • Step count calibration
  • Writing excellent descriptions — the SMIG formula
  • Narrative arc — every tour, every persona
  • Closing steps
  • The 20 personas
  • Designing a tour series
  • What CodeTour cannot do
  • Anti-patterns
  • Quality checklist — verify before writing the file

More skills from github/awesome-copilot

All skills in this repo
  1. acquire-codebase-knowledgegithub/awesome-copilot

    Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.

    40k182 tok idle · 1,945 in use
  2. acreadiness-assessgithub/awesome-copilot

    Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when asked to assess, audit, or score the AI readiness of a repo.

    40k82 tok idle · 678 in use
  3. acreadiness-generate-instructionsgithub/awesome-copilot

    Generate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in the AI Tooling pillar.

    40k77 tok idle · 1,995 in use
  4. acreadiness-policygithub/awesome-copilot

    Help the user pick, write, or apply an AgentRC policy. Policies customise readiness scoring by disabling irrelevant checks, overriding impact/level, setting pass-rate thresholds, or chaining org baselines with team overrides. Use when the user asks about strict mode, AI-only scoring, custom weights, CI gating, or wants org-wide standardisation.

    40k73 tok idle · 879 in use
  5. ad-campaign-analyzergithub/awesome-copilot

    Use this skill when the user shares ad campaign performance data and asks what to cut, scale, or test. Trigger for prompts like "analyze my ad campaigns", "where am I wasting ad spend", "reallocate my ad budget", "which ads are actually working", or "ROAS analysis". Do not trigger for campaign planning or creative generation without performance data.

    40k80 tok idle · 3,472 in use
  6. add-educational-commentsgithub/awesome-copilot

    Add educational comments to the file specified, or prompt asking for file to comment if one is not provided.

    40k27 tok idle · 1,301 in use
  7. adobe-illustrator-scriptinggithub/awesome-copilot

    Write, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate documents, layers, paths, text frames, colors, symbols, artboards, or any Illustrator DOM objects. Covers the complete JavaScript object model, coordinate system, measurement units, export workflows, and scripting best practices.

    40k80 tok idle · 8,741 in use
  8. agent-architecturegithub/awesome-copilot

    Design AI agent architectures through requirements discovery, or audit and diagnose architectural flaws in existing agents. Architecture only; excludes implementation and general code review.

    40k32 tok idle · 1,816 in use