| name | name-audition |
| description | Run candidate product, brand, company, or benchmark names through an audition — authoritative domain-availability checks, collision research across SaaS/GitHub/packages/the target adjacent domain, a light trademark and ownability read, a ranked callback list, and an interactive casting report of finalists with optional draft branding. Use when the user is naming a product, app, company, feature, or benchmark; asks "is this name taken", "check these domains", "help me pick a name", "is X available", "name my product", "brand name research", "audition names"; or wants to compare and pressure-test a shortlist of candidate names before committing. |
Name Audition — «Кастинг имён»
Audition candidate names before you cast one. Brandability is not availability, and a free
domain is not a safe name — the audition separates the three. Candidates try out; the best one
gets cast; the rest simply don't make the cut.
The core lesson this skill encodes
A name can sound perfect, score well, have every domain free — and still be the wrong choice.
Three ways a candidate fails its screen test, worst first:
- Adjacent-domain collision is the worst kind. A product already operating in the target
vertical means a name doesn't make the cut even when the string is free to register —
confusion and SEO dilution are fatal in the same space.
- Descriptive / generic names are domain-free but weak. Easy to register, hard to own — bad
for trademark, bad for SEO, easy for competitors to crowd.
- Search visibility ≠ availability. "I didn't see it in results" is not proof a name is
free. Verify with authoritative sources before casting.
Workflow — the casting call
Run these stages in order. Stages 3a and 3b run together.
- Brief. Establish: (a) what is being named (product / app / company / feature / benchmark),
(b) scope + one-line description, (c) the adjacent domain — the vertical it lives in
(healthcare, coaching, privacy/security, dev tooling); the user supplies this, (d) tone / vibe,
(e) which TLDs matter (default
.com .org .ai .io .app .co). If (a)–(c) is missing, ask first —
the adjacent domain is what makes collision research meaningful.
- The audition. Generate 4–8 candidate names matching the tone. Favor short, pronounceable,
ownable coinages over descriptive compounds. Note for each what it means / why it fits.
- The screen test (run 3a and 3b together):
- 3a — Domains (authoritative). Run
scripts/check_domains.sh NAME [NAME ...] -- com ai io ...
for a name × TLD availability table. WHOIS no-match + no NS = registrable; Creation Date /
Registrar / NS present = taken; ambiguous = verify by hand. Authoritative for registration,
never for trademark.
- 3b — Collision research. For each candidate, use the
firecrawl skill or web search
(never beautifulsoup) to check the sources below.
- Callbacks. Build a per-candidate risk table and rank by safety + ownability.
- Casting report. Use the
present skill to build an interactive HTML deck — one slide per
finalist plus a ranked comparison and a "cast it?" slide.
- Branding (optional, gated). Only if the user wants it: draft a wordmark/logo per finalist
with
nano-banana or gpt-image-2 (draft quality), embed in the slides.
- Cast → user decides. Give a clear top pick with reasoning; the user makes the final call.
Names that fail "didn't make the cut" — never "killed".
Stage 3b — collision research checklist
For each candidate, search these surfaces and record URLs:
- SaaS / AI / startups — Crunchbase, Product Hunt, a plain web search of
"<name>" + vertical.
- Code namespace — GitHub repos literally named it; PyPI and npm packages with that exact name.
- The adjacent domain (most important) —
"<name>" + the user's vertical. A same-vertical hit
is the one that ends an audition.
- Privacy / security tooling — relevant if the thing touches data handling.
- Trademark + ownability — a light USPTO / EUIPO look for live marks in the relevant classes,
plus a judgment call on descriptiveness: distinctive enough to own, or a generic compound a
competitor can crowd?
- Benchmark names — if naming a benchmark, the decisive check is the literature, not domains:
is the name already a published dataset/benchmark (arXiv / ACL / Papers with Code)? Citation
clash, not a domain, is what matters there.
Output table:
| Name | Notable existing uses (URLs) | Adjacent-domain clash? | Trademark / ownability | Verdict |
|---|
| Acme | github.com/x, acme.io (logistics) | No | Distinctive, no live marks | Callback |
Verdict is Callback (advances) / Cut (out) / Cast (the pick). Apply the Decision rules.
Decision rules
- Adjacent-domain collision → Cut. Even if every domain is free. A competing product in the
same vertical poisons the name.
- Descriptive / generic compound → weak. Domains may be free, but hard to trademark and bad for
SEO. Flag the ownability risk even when registrable.
- Domains-free ≠ safe. Availability is necessary, not sufficient. A name earns the part only
when it is both registrable and clear of adjacent-domain and trademark collisions.
- Verify before casting. Confirm domains with
check_domains.sh and trademark with a registry
lookup, not with "I didn't find anything."
- Rank by safety first, then ownability, then aesthetics.
Example (a real audition)
Naming a privacy-focused de-id toolkit + benchmark for the mental-health / coaching vertical.
Audition: Praxio, Dyad, Sessio, ClientPII, CONFIDE.
| Name | Screen test | Verdict |
|---|
| Praxio | Sounded great, but Praxis EMR is a mental-health EHR — adjacent-domain collision in the exact vertical. | Cut |
| Dyad | Clean, meaningful, but dyad.sh is a local-AI dev tool and dyad.ai is a healthcare company — collisions in both tech and the vertical. | Cut |
| Sessio | Nice, but sessio.base44.app is a same-vertical product for therapists. | Cut |
| ClientPII | All TLDs free — but a generic descriptive compound, weak to trademark, bad SEO. | Didn't make the cut (as a brand) |
| CONFIDE | Domains all taken (bad product brand) — but as a benchmark name, citation-collision is low. | Cast (as the benchmark name) |
One line: domains-free ≠ safe, and brandable ≠ available. Most names that look good fail on
adjacent-domain collisions a domain check alone would never catch.
scripts/check_domains.sh
scripts/check_domains.sh praxio dyad sessio
scripts/check_domains.sh praxio dyad -- com ai io
TLDS="com org ai" scripts/check_domains.sh praxio
Per domain it runs whois (following the IANA registry referral when needed) plus dig +short NS,
printing a name × TLD table of free / taken / ?. ? = verify by hand (WHOIS rate-limit or
.ai flakiness). Needs whois and dig on PATH (ship with macOS; apt install whois dnsutils).
Referenced skills
firecrawl — collision / literature research (stage 3b). Never beautifulsoup.present — interactive HTML casting report (stage 5). Pass it the comparison + per-name slides.nano-banana or gpt-image-2 — optional draft branding (stage 6). Draft quality by default.
Safety & limits
- WHOIS is authoritative for registration, not trademark. A free domain can still infringe a
live mark. Always do the separate trademark read.
.ai WHOIS is flaky. Treat ? as "check the registrar's search," not "free."- The script proves registrability, not legal clearance — no trademarks, social handles, or
app-store conflicts. For a name you'll build a business on, get an attorney's clearance.
- Branding is optional and gated — generate logos only when the user asks; draft quality unless
told otherwise.
- The user casts. The skill recommends; it does not commit.
Install
Portable across Claude Code and Codex — plain-prose workflow, one bash script, no Claude-only tools.
cp -R name-audition ~/.claude/skills/
cp -R name-audition ~/.agents/skills/
