The Naming Strategist
A metaphor-driven, structured process for naming products, SaaS, and brands — with AI-slop names actively filtered out.
allowed-tools are scoped to read-only operations (Read/Grep/Glob, whois, npm view, gh repo view, WebSearch/WebFetch); no writes, deletions, or credential access. Data flow is transparent: candidate names are sent via whois/curl/search to external services, clearly stated. Deductions: external network queries (which reveal the user's naming intent) require no explicit user confirmation; no explicit sensitive-data handling note; no rollback/recovery guidance; publisher unverified but not deducted per rules. ~8 points deducted.
Process is self-consistent: 7 steps, explicit loop-back conditions, a mandatory availability gate (Step 5) with fallbacks (curl when whois missing). Deductions: the bundled check-availability.sh source is not in evidence, so its behavior cannot be statically confirmed; no tests; thin edge/abnormal-input handling; whois/curl are network-sensitive and error-prone (availability.md itself admits false positives). Static cap of 10 applies; scored 9.
Trigger semantics are clear: description names target objects (products/SaaS/brands/open source/bots), Step 1 defines inputs, Step 7 defines output format, with boundaries implied. Deductions: skill is English-centric; language files cover only Polish and Portuguese — no Chinese support; core availability checks depend on whois and overseas services (npm, PyPI, GitHub, t.me, WordPress API) whose reachability from mainland China is questionable. ~6 points deducted.
Good layering: SKILL.md as entry point only, explicit context-budget management, on-demand reference loading table; README install docs; MIT license, branch protection, markdownlint and link-check CI, detailed CONTRIBUTING with maintainer response expectations (solo maintainer, 1-2 weeks). Deductions: no version number, no CHANGELOG, no known-limitations section. ~3 points deducted.
The core task (availability-verified finalists with origin stories) is well designed with genuine marginal value via AI-slop filtering and mandatory availability checks. Deductions: static review cannot verify actual output quality; final results still need user trademark/legal diligence; the checks themselves admit false positives requiring manual verification. Static cap of 7; scored 6.
Some auditable primary material: case studies require verifiable sources, CI includes lint and link-check workflows, contributing guide requires sourced facts. Deductions: no test suite, no execution evidence; the recall statistic (68.8% vs 38.1%) lacks a citable source; most reference files are not included in the evidence. Static cap of 5; scored 4.
- Availability checks depend on whois and multiple overseas services (npm, PyPI, GitHub, t.me, etc.), which may be unreachable or time out from mainland-China networks, blocking or corrupting Step 5.
- The source of check-availability.sh is not included in this review's evidence; its behavior, exit codes, and false-positive modes cannot be statically verified — read it manually before use.
- Availability queries send candidate names to external services, potentially exposing not-yet-public naming intent; for confidential projects consider skipping or manually running checks.
- The skill is English-centric with no Chinese language file; applicability to Chinese-language brand naming is limited.
- No version numbers or changelog exist, so content changes between updates cannot be determined.
What does this skill do, and when should you use it?
This Claude Code skill turns the AI into a naming strategist, running a seven-step process to name products, SaaS tools, brands, open source projects, and apps. It starts with a naming brief and explores metaphor territories instead of querying a thesaurus. Candidate generation, filtering, availability checking, and scoring all happen autonomously mid-process — the user only sees a vetted shortlist of 3-5 names with verified availability. The skill ships 14 on-demand reference files plus a bundled script that batch-checks domains, npm, PyPI, GitHub, Telegram, and more.
Establishes a naming brief by asking six questions (function, audience, feel, platform targets, etc.); loads only the needed files from 14 references (metaphor-mapping.md, principles.md, etc.) to explore metaphor territories and generate 30-50+ candidates; filters out AI slop like -ly/-ify suffixes via an anti-pattern checklist; runs the bundled scripts/check-availability.sh plus whois, curl, npm view, and WebSearch to actually verify availability on domains, npm, PyPI, GitHub, crates.io, RubyGems, WP plugin slugs, and Telegram; finally presents a weighted-scored shortlist with origin stories, availability status, and tagline suggestions.
What are this skill's strengths and limitations?
- Concrete methodology: 7-step process, weighted scoring rubric, anti-pattern checklist — not generic advice.
- Mandatory real availability checks using whois/curl/npm tools rather than guessing from memory.
- Well-designed context management: 15+ reference files load on demand; a simple task loads only 2-3 files.
- Loop-back mechanism: when candidates fail or score under 70, it returns to earlier steps instead of lowering the bar.
- MIT licensed and open source, welcoming language and industry guide contributions.
- Built for Claude Code — the /naming slash command and allowed-tools frontmatter need adaptation for other platforms.
- Availability checks depend on local commands (whois, curl, gh, npm) and network; without them, check quality degrades, and a whois failure falls back to merely testing whether a site is live.
- No test suite or sample end-to-end naming outputs are shown in the source, so real-world results are independently unverified.
- The core claim (real-word names ~68.8% recall vs ~38.1% for invented names) is cited without a source in the provided material.
How do you install this skill?
Clone the repo into a Claude Code skills directory. Project-level: mkdir -p .claude/skills && git clone https://github.com/glacierphonk/naming.git .claude/skills/naming. Personal (all projects): mkdir -p ~/.claude/skills && git clone https://github.com/glacierphonk/naming.git ~/.claude/skills/naming. Claude Code must already be installed.
How do you use this skill?
Type /naming in Claude Code and describe what you need a name for in one sentence, or just describe the challenge in conversation — Claude loads the relevant references automatically. Availability checking requires local commands (whois, curl, gh, npm) and network access; platforms the script doesn't cover (app stores, social handles) are checked via WebSearch. A quick session loads only 2-3 reference files.