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/viknesh20-20/claude-code-tool-kit/reference-appnpx skills add viknesh20-20/claude-code-tool-kit --skill reference-appgit clone --depth 1 https://github.com/viknesh20-20/claude-code-tool-kitWhat 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 | $0.00054 | $0.01435 |
| Opus 5 | $0.00027 | $0.00718 |
| Sonnet 5 | $0.00011 | $0.00287 |
| Haiku 4.5 | $0.00005 | $0.00144 |
Grade A, and why
reference-app 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.
How it starts
The opening of the file, as written. The whole thing — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/reference-app
Point Claude at another fully-developed application the user wants to use as a reference. Build a structured understanding of it. Store that understanding in memory so future sessions can compare the current project against it.
When to use
- The user is starting a new project and wants it modeled on one they've already built.
- The user is reviewing the current project's code and wants you to compare it against an existing well-built example.
- The user is migrating, refactoring, or modernizing and the reference app shows the destination state.
- The user wants you to "understand" their full app even though you're working in a different directory today.
Operating method — ASK FIRST, THEN ANALYZE
Step 0: Confirm intent.
Before reading anything, ask:
- "What would you like me to learn from this reference app?" — pattern conventions / architecture / specific module / all of it.
- "What does the current project share with the reference?" — same domain / same stack / similar feature / different / unsure.
- "Should I treat the reference as authoritative (apply its patterns here) or as inspirational (consider its patterns)?"
These three answers shape the depth and tone of the resulting memory. Don't skip them.
Step 1: Validate the path.
- Confirm the path exists and is readable.
- Check it has a recognizable project structure (package.json, pyproject.toml, go.mod, Cargo.toml, etc.). If not, ask the user what kind of project it is.
Step 2: High-level scan (light pass).
Read in this order, one file each, no deep dives yet:
- Top-level README.
CLAUDE.mdif it exists.- The package/dependency manifest.
- The deployment / CI config.
- The directory tree (one level deep, maybe two).
Step 3: Architecture map.
- Identify the entry points (server start, client root, CLI commands).
- Identify the main modules and their responsibilities (one sentence each).
- Identify external dependencies that matter to the architecture (DB, queue, cache, auth, payment, etc.).
- Identify the testing approach (framework, layering).
- Identify the deploy target.
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 · 171 lines · 54 tokens per session scan A fa5c57a8a383
reference-app is a skill published in the GitHub repository viknesh20-20/claude-code-tool-kit (7 stars, last pushed 4mo ago), licensed MIT. It adds 54 tokens to every session and 1,435 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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