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 skills add sandeepmvl/rails-skills --skill 59-scaffold-project-skillsgit clone --depth 1 https://github.com/sandeepmvl/rails-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/sandeepmvl/rails-skills/59-scaffold-project-skills)<a href="https://agentmods.dev/skills/sandeepmvl/rails-skills/59-scaffold-project-skills"><img src="https://agentmods.dev/badge/skills/sandeepmvl/rails-skills/59-scaffold-project-skills/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/sandeepmvl/rails-skills/59-scaffold-project-skills"><img src="https://agentmods.dev/badge/skills/sandeepmvl/rails-skills/59-scaffold-project-skills.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00142 | $0.02426 |
| Opus 5 | $0.00071 | $0.01213 |
| Sonnet 5 | $0.00028 | $0.00485 |
| Haiku 4.5 | $0.00014 | $0.00243 |
Grade B, and why
scaffold-project-skills scanned grade B with 1 finding 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 9d 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.
Enumerates other installed skillsmediumAgent snooping
Other skills' SKILL.md files reveal prompts, capabilities and secrets that should be invisible to peers.
ls .claude/skills 2>/dev/null; sed -n '1,40p' CLAUDE.md 2>/dev/null How it starts
The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scaffold Project-Specific Skills
The generic
rails-skillspack teaches an agent how senior Rails devs write Rails. It cannot know your product — your tenant isolation rules, your booking/payment workflow, your test-and-verify loop. This skill closes that gap: it interviews your app and generates local, project-specific skills that live in your repo and become the source of truth. Use the generic pack as the baseline; use the skills this generates as the authority.
Why this matters
A general Rails pack steers toward generic "best practice." But your hard parts are domain-specific: which models are tenant-scoped, what a valid Offer looks like, how a draft gets accepted, what your team's verification loop actually is (e.g. inspect → implement → Playwright, not RSpec-first). When those rules live only in people's heads, every AI agent re-derives them — and gets them subtly wrong.
The fix is local skills: small, product-aware SKILL.md files in your own .claude/skills/ that encode the conventions that matter to your launch. This skill scaffolds them from an interview + a codebase scan, so you start from a real draft instead of a blank file.
The opinion
Keep project-specific skills in your own repo as the source of truth; let the generic pack be the fallback. Generate them from the actual codebase, not a wish-list. One skill per bounded product area (tenancy, a domain workflow, your verification loop) — small and high-signal beats one giant "conventions" file. Encode rules an agent can act on, and prefer a checker (test, lint, gate) over prose wherever a rule can exit 0/1.
Counter-position: some teams put everything in a single root CLAUDE.md. That works for a while, but as one file grows, per-rule attention tends to degrade — the agent honors the top and bottom more reliably than the middle. Splitting into description-gated skills (so only the relevant rules load per task) is more dependable than relying on one long instruction file, regardless of its exact length.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 155 lines · 142 tokens per session scan B fdd654483e3c
scaffold-project-skills is a skill published in the GitHub repository sandeepmvl/rails-skills (21 stars, last pushed 3mo ago), licensed MIT. It adds 142 tokens to every session and 2,426 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it B with 1 finding (enumerates other installed skills). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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