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 KhaledSaeed18/dotclaude --skill project-name-checkgit clone --depth 1 https://github.com/KhaledSaeed18/dotclaudeWrote 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/khaledsaeed18/dotclaude/project-name-check)<a href="https://agentmods.dev/skills/khaledsaeed18/dotclaude/project-name-check"><img src="https://agentmods.dev/badge/skills/khaledsaeed18/dotclaude/project-name-check.svg" alt="Measured on agentmods" 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 | $0.00072 | $0.01763 |
| Opus 5 | $0.00036 | $0.00881 |
| Sonnet 5 | $0.00014 | $0.00353 |
| Haiku 4.5 | $0.00007 | $0.00176 |
Grade A, and why
project-name-check 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 7d 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Clear a name before it gets stamped into a repo, a package manifest, a domain, and a logo. The whole skill rests on one rule: a name is only "available" where you checked it, with evidence you can show. Registry APIs and RDAP answer definitively; search engines do not. Report what you verified, name what you could not, and never round an unchecked surface up to "free".
You investigate and report. You do not register, purchase, publish, or reserve anything.
This skill covers the surfaces a shipped artifact lives on. If the name is for a company, a product brand, or a storefront, the surfaces that decide it are social handles, commerce platforms, company registers, and trademarks: use the business-name-check skill for that, or run both when the project and the company share a name.
Step 1: Frame the check
Work out three things before searching. Infer what you can from the working directory (package.json, pyproject.toml, Cargo.toml, go.mod, *.xcodeproj, manifest.json, README, git remote) and only ask about what is genuinely unknowable.
- The candidates. Push for three to five, not one. A single candidate turns this into a yes/no with no fallback, and the first choice is usually taken. If the user has only one, check it first and generate variants in step 5 if it fails.
- What ships, and where. An npm package, a Homebrew CLI, a Mac App Store app, a VS Code extension, a Python library, a hosted product, or several at once. This picks the surfaces in step 2 and nothing else does.
- How much the name must carry. A throwaway internal tool needs a namespace collision check. A public product that will get a domain, a logo, and search traffic needs the full sweep including competitors and trademark signals.
State the resolved framing back in one or two lines before you start burning searches, so a wrong assumption gets corrected cheaply.
Step 2: Pick the surfaces
Open docs/surfaces.md and assemble the check list: every universal surface, plus the ecosystem surfaces that match how this thing ships. Skip surfaces that cannot apply (no App Store check for a Python library) and say in the report that you skipped them and why.
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.
- 7d ago First seen · 100 lines · 72 tokens per session scan A 627035c904a7
project-name-check is a skill published in the GitHub repository KhaledSaeed18/dotclaude (5 stars, last pushed 6d ago), licensed MIT. It adds 72 tokens to every session and 1,763 once invoked, about $0.0004 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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