Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/nklofy/code-agent-skills/code-tournpx skills add nklofy/code-agent-skills --skill code-tourgit clone --depth 1 https://github.com/nklofy/code-agent-skillsWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00053 | $0.01676 |
| Opus 5 | $0.00026 | $0.00838 |
| Sonnet 5 | $0.00011 | $0.00335 |
| Haiku 4.5 | $0.00005 | $0.00168 |
Grade A, and why
code-tour scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
86% identical to ecc-code-tour — 28 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 238 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Tour
Create CodeTour .tour files for codebase walkthroughs that open directly to real files and line ranges. Tours live in .tours/ and are meant for the CodeTour format, not ad hoc Markdown notes.
A good tour is a narrative for a specific reader:
- what they are looking at
- why it matters
- what path they should follow next
Only create .tour JSON files. Do not modify source code as part of this skill.
When to Use
Use this skill when:
- the user asks for a code tour, onboarding tour, architecture walkthrough, or PR tour
- the user says "explain how X works" and wants a reusable guided artifact
- the user wants a ramp-up path for a new engineer or reviewer
- the task is better served by a guided sequence than a flat summary
Examples:
- onboarding a new maintainer
- architecture tour for one service or package
- PR-review walk-through anchored to changed files
- RCA tour showing the failure path
- security review tour of trust boundaries and key checks
When NOT to Use
| Instead of code-tour | Use |
|---|---|
| A one-off explanation in chat is enough | answer directly |
The user wants prose docs, not a .tour artifact |
documentation-lookup or repo docs editing |
| The task is implementation or refactoring | do the implementation work |
| The task is broad codebase onboarding without a tour artifact | codebase-onboarding |
Workflow
1. Discover
Explore the repo before writing anything:
- README and package/app entry points
- folder structure
- relevant config files
- the changed files if the tour is PR-focused
Do not start writing steps before you understand the shape of the code.
2. Infer the reader
Decide the persona and depth from the request.
| Request shape | Persona | Suggested depth |
|---|---|---|
| "onboarding", "new joiner" | new-joiner |
9-13 steps |
| "quick tour", "vibe check" | vibecoder |
5-8 steps |
| "architecture" | architect |
14-18 steps |
| "tour this PR" | pr-reviewer |
7-11 steps |
| "why did this break" | rca-investigator |
7-11 steps |
| "security review" | security-reviewer |
7-11 steps |
| "explain how this feature works" | feature-explainer |
7-11 steps |
| "debug this path" | bug-fixer |
7-11 steps |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 238 lines · 53 tokens per session scan A b115de452cfd
code-tour is a skill published in the GitHub repository nklofy/code-agent-skills (18 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 53 tokens to every session and 1,676 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to ecc-code-tour, differing in 28 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…