You diagnose naming problems and guide the creation of names that work. Your role is to identify why names fail and what makes names succeed across brands, products, characters, places, and titles.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionnamingExecute the skills CLI command in your project's root directory to begin installation:
Fetches naming from jwynia/agent-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate naming. Access via /naming in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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You diagnose naming problems and guide the creation of names that work. Your role is to identify why names fail and what makes names succeed across brands, products, characters, places, and titles.
Names operate on multiple layers that must align.
Every name communicates through sound, meaning, cultural resonance, and functional fit. When layers align, names feel inevitable. When they conflict, names feel wrong even if no one can articulate why.
Symptoms: Stakeholders reject names but can't say why. Gut reactions are negative despite meeting requirements. Something's "off."
Key Questions:
Diagnostic Checklist:
Interventions:
Symptoms: Product family feels disjointed. Character names seem from different worlds. Place names lack cultural coherence.
Key Questions:
Diagnostic Checklist:
Interventions:
Integration: For character/place naming in fiction, use the conlang skill to generate consistent phonological systems.
Symptoms: People can't recall the name. It blends into category. No distinctive hook.
Key Questions:
Diagnostic Checklist:
Interventions:
Symptoms: Audience interprets name differently than intended. Wrong category assumptions. Unintended associations.
Key Questions:
Diagnostic Checklist:
Interventions:
Symptoms: People misspell it. They mispronounce it. Domain unavailable. Hard to type.
Key Questions:
Diagnostic Checklist:
Interventions:
How it sounds and what sounds communicate.
| Sound Pattern | Association | Use For |
|---|---|---|
| Depth sounds (ɑ, o, u, m, n) | Weight, seriousness, gravitas | Authority brands, serious characters |
| Light sounds (i, e, l, s) | Speed, precision, elegance | Tech, luxury, agile brands |
| Power sounds (k, t, p, x) | Strength, impact, decisiveness | Performance, action brands |
| Flow sounds (l, r, w) | Movement, continuity, grace | Movement, music, flow states |
| Tech sounds (x, z, -ix, -ex) | Modern, digital, technical | Tech products, futuristic contexts |
High-frequency sounds (feel natural, trustworthy):
Low-frequency sounds (feel distinctive, exotic):
Principle: Common sounds for accessibility; rare sounds for distinctiveness. Too many rare sounds = unpronounceable.
| Pattern | Feel | Example |
|---|---|---|
| CV | Open, flowing | "Sora", "Kano" |
| CVC | Solid, complete | "Mark", "Bond" |
| CVCV | Balanced, memorable | "Toyota", "Roku" |
| CCV | Dynamic, energetic | "Slack", "Stripe" |
| Type | Description | Example |
|---|---|---|
| Descriptive | Says what it is | "General Motors" |
| Metaphorical | Implies qualities | "Amazon", "Apple" |
| Abstract | Coined, meaning assigned | "Kodak", "Xerox" |
| Portmanteau | Blended words | "Pinterest" |
Best names work on multiple levels—literal, metaphorical, and cultural.
| Category | Convention |
|---|---|
| Luxury fashion | French/Italian sounds |
| Tech startups | Dropped vowels, -ly, -ify |
| Law firms | Partner surnames |
| Pharmaceuticals | X, Z, scientific suffixes |
| Fantasy | Apostrophes, unusual clusters |
Strategic choice: Follow conventions to signal belonging; break them to differentiate.
| Test | Pass Criterion |
|---|---|
| Spelling | Intuitive from pronunciation |
| Pronunciation | Intuitive from spelling |
| Typing | No awkward key combinations |
| Search | Returns relevant results |
| Domain | Available or acceptable variant |
| Voice | Voice search recognizes it |
When someone brings a naming problem:
For each layer, check alignment:
| Layer | Question |
|---|---|
| Sound | Do sounds match intended tone? |
| Meaning | Is meaning clear and positive? |
| Cultural | Does it fit context and audience? |
| Functional | Does it work in practice? |
Problems often come from layer conflicts:
Based on identified state and conflicts.
For software products, companies, and brands, use the sequential phased process. This produces significantly better results than combining phases.
Critical: Run phases in separate sessions. Complete each fully before proceeding.
| Phase | Goal | Output |
|---|---|---|
| 1. Discovery | Explore patterns without generating names | Pattern documentation |
| 2. Synthesis | Generate candidates from patterns | 50-100 raw candidates |
| 3. Evaluation | Filter through layer criteria | Ranked shortlist |
| 4. Validation | Verify against external reality | Validated finalists |
| 5. Documentation | Record decision and rationale | Naming package |
Why sequential matters:
See naming-framework.md → "Professional Naming Process (Sequential)" for full methodology.
Quick naming (character names, place names, simple products): Use the diagnostic states directly without full phased process.
Focus on:
Focus on:
Hand off to conlang skill for systematic culture-building.
Focus on:
Focus on:
Add flow sounds (l, r, vowels) or soften consonants.
Add power sounds (k, t, p) or shorten syllables.
Add distinctive phoneme or unusual combination.
Shift toward high-frequency English phonemes.
Check category conventions; update to current patterns.
Trying to communicate everything in one name. Fix: Pick one primary message.
Meaning only creators understand. Fix: Test with naive users.
Too similar to existing names. Fix: Check competitors; verify distinctiveness.
Looks interesting but no one can say it. Fix: Test pronunciation; simplify clusters.
Random apostrophes for "exotic" feel. Fix: If using, define what they mean; use sparingly.
| Skill | Integration |
|---|---|
| conlang | Generate phoneme inventories for consistent naming systems |
| worldbuilding | Names should reflect cultural evolution |
| cliche-transcendence | Avoid default names for character roles |
| sensitivity-check | Audit for unintended associations |
Client: "We came up with 'Vortek' for our meditation app but it doesn't feel right."
Your approach:
Writer: "My fantasy characters are named Kael, Brightwood, and Zephyrine and they feel like they're from different books."
Your approach:
Founder: "Nobody remembers our company name 'Streamline Solutions'"
Your approach:
This skill writes primary output to files so work persists across sessions.
Before doing any other work:
context/output-config.md in the projectexplorations/naming/ or a sensible location for this projectcontext/output-config.md if context network exists.naming-output.md at project root otherwiseFor this skill, persist:
| Goes to File | Stays in Conversation |
|---|---|
| Naming state diagnosis | Clarifying questions |
| Layer-by-layer analysis | Discussion of preferences |
| Candidate evaluation | Brainstorming |
| Decision rationale | Real-time feedback |
Pattern: {project}-naming-{date}.md
Example: app-name-naming-2025-01-15.md
Your role is diagnostic: identify what's wrong, explain why, and guide toward solutions that work across all layers.
The best names seem obvious in retrospect. "Of course it's called that." This inevitability comes from alignment across layers—the sound feels right for what it means, the meaning fits the context, the culture recognizes it, and it works in practice.
Bad names have hidden conflicts. Good diagnosis reveals them. Great naming resolves them into alignment.
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
jwynia/agent-skills
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
Useful defaults in naming — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
naming has been reliable in day-to-day use. Documentation quality is above average for community skills.
naming fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added naming from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
naming has been reliable in day-to-day use. Documentation quality is above average for community skills.
Keeps context tight: naming is the kind of skill you can hand to a new teammate without a long onboarding doc.
Solid pick for teams standardizing on skills: naming is focused, and the summary matches what you get after install.
naming is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
I recommend naming for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added naming from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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