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 agentmods add skills/jbold/namer/namernpx skills add jbold/namer --skill namergit clone --depth 1 https://github.com/jbold/namerWrote 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/jbold/namer/namer)<a href="https://agentmods.dev/skills/jbold/namer/namer"><img src="https://agentmods.dev/badge/skills/jbold/namer/namer.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 | $0.00048 | $0.01714 |
| Opus 5 | $0.00024 | $0.00857 |
| Sonnet 5 | $0.00010 | $0.00343 |
| Haiku 4.5 | $0.00005 | $0.00171 |
Grade A, and why
namer 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 3d 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Namer
Structured naming pipeline for any product, company, or brand. Uses the Diamond Framework (David Placek / Lexicon Branding) for strategy, then leverages LLM knowledge of languages, cultures, history, and sound symbolism to generate and evaluate candidates.
Pipeline: Discover → Seeds → Generate → Evaluate → Verify → Present
Step 1: Discover
Ask these 5 questions one at a time, in order:
1. What's the domain? — "What industry or category is this?" (e.g. coffee shop, developer tool, law firm, band)
2. What does winning look like? — The vision. What is this, who's it for, what does success look like?
Swiffer: "Build a mop-like device people pay a premium for. Make cleaning floors something people want to do."
3. What do we have to win? — The advantage. What assets or insights give you an edge?
Swiffer: "P&G's Pampers diaper tech — a lighter, more effective tool using absorbent pads instead of water."
4. What do we need to win? — The gaps. What's missing? What must be overcome?
Swiffer: "Avoid being seen as just another mop. People hate mopping — they need to see this as entirely new."
5. What do we need to say? — The message. What should the name communicate? What should it feel like?
Swiffer: "Logical: efficient, quick, easy. Emotional: fun, joyful, light. Should sound like a quick, satisfying action."
See references/diamond-framework.md for the full framework with case studies.
Step 2: Extract Seeds
From the user's answers, extract 30-50 seed words:
Literal seeds (~15-25):
- ~3-5 from domain vocabulary
- ~3-5 from "winning" (vision/ambition)
- ~3-5 from "have to win" (differentiators)
- ~2-3 from "need to win" (aspirations)
- ~3-5 from "need to say" (feeling/tone)
Evocative seeds (~15-25) — generate these yourself:
- Metaphorical — words from adjacent domains (nature, mythology, architecture, music, materials). "If this product were a natural phenomenon, what would it be?"
- Cross-cultural roots — Latin, Greek, Sanskrit, Japanese, Arabic roots carrying the right connotation
- Sound-designed — invented syllable combos chosen for phonetic personality
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.
- 3d ago First seen · 128 lines · 48 tokens per session scan A 8c5424dbd698
namer is a skill published in the GitHub repository jbold/namer (5 stars, last pushed 6mo ago), licensed MIT. It adds 48 tokens to every session and 1,714 once invoked, about $0.0002 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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