# Brand Name Research > Brand Name Research - Skill: `ronniepinnell/brand-name-research` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add ronniepinnell/brand-name-research` - Raw SKILL.md: https://api.skillmd.com/api/skills/ronniepinnell/brand-name-research/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Research & Search - Author: ronniepinnell (https://skillmd.com/u/ronniepinnell) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/ronniepinnell/brand-name-research --- # Brand Name Research Turn a multi-hour, repetitive naming slog into one guided pass. The golden rule: **never raise hopes on a name that won't survive.** Only fully-screened, PASSING names are shown — taken ones are filtered out silently (with a count of how many died). ## Operating principle: passive checks only (no front-running) Domain "search" boxes on registrars (GoDaddy, Namecheap, etc.) and their availability APIs can **log your query and get the domain front-run** (someone registers it before you do). This skill NEVER touches those. It only uses: - `dig` / `whois` (DNS + registry lookups — read-only, no "search intent" leaked) - Public read APIs: iTunes Search API (App Store), npm registry, PyPI, GitHub profile pages - `WebSearch` / `WebFetch` for Play Store, trademarks, existing companies, social handles When the user picks a winner, tell them to **register the .com (and chosen TLDs) immediately** through a real registrar — don't sit on it. --- ## Phase 0 — Inputs If `--check "name1,name2"` is passed: skip Phases 1–2, go straight to screening those. If `--from-readme ` (or a `*/README.md` is obviously relevant): read it to seed the grill, then still confirm the gaps below. --- ## Phase 1 — Grill me (the interview) Use `AskUserQuestion`. Keep it to 2 batches. Skip anything already known from a README. **Batch A — the product & the vibe** 1. **What is it, in one sentence?** (who it's for + what it does) — *prefill from README if given.* 2. **Market / category?** (e.g. dev tools, hockey analytics, fintech, consumer notes app) — this defines "same-market collisions" to reject. 3. **Name style** (multi-select): real word · coined/invented · compound (two words) · misspelling/respelling · metaphor/evocative · short & abstract · person/place · acronym. 4. **Vibe / adjectives** — 3–5 words it should feel like (e.g. "fast, sharp, technical" or "warm, playful, human"). Names you already like (any field) to triangulate taste. **Batch B — hard constraints** 5. **Desired TLDs**, in priority order (e.g. `.com` required, then `.io`, `.dev`, `.ai`). Note if `.com` is mandatory or just preferred. 6. **Length / syllables** ceiling (e.g. ≤ 7 letters, ≤ 2 syllables, "must be typeable"). 7. **Must include / must avoid** — letters, sounds, words, themes. Languages to avoid bad connotations in. Competitors whose names it must NOT resemble. 8. **Channels that must be clean** (multi-select): domain · Apple App Store · Google Play · US trademark · GitHub org · npm · PyPI · X/Twitter handle · Instagram handle. (Only these are treated as PASS-blocking; others are "nice to have, reported.") Echo back a 4–6 line **naming brief** and get a thumbs-up before generating. --- ## Phase 2 — Generate candidates Brainstorm **40–60** candidates matching the brief. Use varied techniques so the pool is diverse, not 50 variations of one root: - Real words & evocative metaphors from the product's domain. - Coined words (blend two roots; add suffixes -ly, -ify, -io, -ory, -al; drop vowels). - Compounds (Adjective+Noun, Noun+Noun) and clipped compounds. - Greek/Latin/other-language roots tied to the concept (sanity-check meaning). - Sound-symbolism matching the vibe (plosives = sharp/fast; liquids/nasals = smooth/calm). Internally note each candidate's style + why it fits. Do **not** show the raw 60 yet — they haven't been screened. --- ## Phase 3 — Screen (passive, batched) > **ORDER MATTERS: go BROAD before NARROW.** The #1 failure mode of this skill is trusting > the App Store API + a market-qualified search and declaring a name "clean" — then a plain > Google of the bare word instantly surfaces a Google-Play/international app, an apparel > label, a crypto token, or a supplement vendor on the exact name. **Always run the broad > gut check (3a) FIRST and let it kill names before you spend lookups on anything else.** ### Phase 3a — BROAD GUT CHECK (mandatory, runs first, no market qualifier) For EVERY surviving candidate, before any other check: 1. **Bare-word web search** — `WebSearch ""` and `WebSearch " app"`. - Do **NOT** append your market keyword here ("fitness", "hockey", etc.). Broad first — you're looking for *anyone at all* on the exact string. A market qualifier hides collisions in adjacent categories (apparel, crypto, supplements, gaming, music). - Read the top ~10–15 results and **catalog every exact-spelling entity in ANY category**: apps (iOS **and** Android **and** web, any country), companies/startups, clothing/merch brands, crypto tokens, supplement/peptide vendors, bands/musicians, gamers/streamers, products. Note what each is + how active/prominent. 2. **App stores, both, explicitly** — `WebSearch " site:play.google.com"` AND `WebSearch " site:apps.apple.com"`. The iTunes API in the script misses Google Play and many international iOS apps — this catches them. 3. **Socials sweep (always run, not just if selected)** — WebFetch each for 404-vs-profile: `x.com/`, `instagram.com/`, `tiktok.com/@`, `youtube.com/@`, `twitch.tv/`, `github.com/`. Report which exact handles are taken and by whom. **Reject in 3a (hard FAIL) if any of:** an exact-name app exists on *any* store; a *prominent* global brand owns the word; **any** entity uses the exact name **in or adjacent to the product's category** (for a fitness app that includes activewear, supplements, wearables, sports gear, gyms, athletes); or the name is so widely used that it's effectively un-ownable. A few tiny unrelated entities in far-off categories are acceptable but must be **reported, not hidden** — the user decides. Only names that survive 3a proceed to 3b. ### Phase 3b — Structured checks (only on 3a survivors) Run the bundled screener: ```bash scripts/check-name.sh "" --tlds ``` It reports per-candidate: domain status per TLD, Apple App Store match, GitHub/npm/PyPI, and a final `VERDICT: PASS|FAIL`. Run candidates in batches (independent — fire several Bash calls in parallel). Then: - **Existing company in the same market** — NOW you may add the market keyword: `WebSearch " "` → a real player in the category = reject. - **US trademark** (if selected): `WebSearch " trademark"` or check `tmsearch.uspto.gov`; flag live marks in related classes. (Advisory, not legal advice.) - **Domains/handles**: confirm the specific TLDs and the exact handles you'd actually use. A candidate **PASSES** only if (a) it cleared the broad gut check 3a, and (b) every channel the user marked PASS-blocking (Phase 1 Q8) is clear. Keep a tally: `screened N → M passed`, and note *why* each died (broad-search collision / app / domain / company / trademark). --- ## Phase 4 — Deliver only survivors Aim to present **8–15 PASSING names** (generate another batch and re-screen if too few). Rank by fit to the brief (vibe + style + length + how clean across channels). Output a table — every row is a name that already survived screening (incl. the 3a broad gut check): | Name | Style | Why it fits | Broad web (any exact-name entity?) | .com | other TLDs | App stores (iOS+Play) | TM signal | Handles | |------|-------|-------------|------------------------------------|------|-----------|-----------------------|-----------|---------| | Saber | real word | sharp, fast, technical | only a tiny unrelated EU firm | ✅ free | .io ✅ .dev ✅ | clear both | none seen | @saber taken→@saberhq ✅ | Then: - **Top 3 picks** with a one-line rationale each. - **Footer**: "Screened {N} candidates, {N−M} eliminated (apps/domains/companies)." - **Action**: "Register the .com + chosen TLDs now before sharing the name anywhere — searches elsewhere can tip off squatters." Offer to: save the report to the product folder (`Write` a `NAMING.md` next to the README), run another round with a tweaked brief, or deep-dive trademark on a finalist. --- ## Notes & limits - DNS-clear is a strong but not 100% signal a domain is unregistered (rarely, a registered domain has no DNS); the screener confirms with `whois`. Conservative by design — it would rather call a free name "registered" than the reverse. - Trademark output is a **signal, not legal clearance**. For anything you'll build a business on, do a proper search / consult counsel before filing. - This skill checks availability and collisions; it does not register anything. ## Judgment weave (see /judgment) - **Before delivering the winner:** names are **`/door`** territory — one-way once shipped. Enumerate the lock-in (domains bought, handles claimed, SEO) before the user commits.