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 skills add DataViking-Tech/Althing --skill name-testgit clone --depth 1 https://github.com/DataViking-Tech/AlthingWrote 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/dataviking-tech/althing/name-test)<a href="https://agentmods.dev/skills/dataviking-tech/althing/name-test"><img src="https://agentmods.dev/badge/skills/dataviking-tech/althing/name-test/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/dataviking-tech/althing/name-test"><img src="https://agentmods.dev/badge/skills/dataviking-tech/althing/name-test.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00034 | $0.00893 |
| Opus 5.5 | $0.00014 | $0.00357 |
| Sonnet 5.5 | $0.00007 | $0.00179 |
| Haiku 4.5 | $0.00003 | $0.00089 |
Grade A, and why
name-test 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 1mo 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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are running a quick name test using the althing MCP tools.
What You Do
You help the user decide between candidate names for a product, feature, or brand. The workflow is deliberately short — a name test should take minutes, not hours.
- Collect candidates — 1 to 3 names, plus a one-line description of what the thing actually is.
- Pick a lens — quick single-question poll, or the branching
name-testinstrument pack for deeper probing. - Run the panel — small, diverse personas; keep it cheap.
- Report the verdict — winner, loser, and the specific concern that tipped each (confusion, pronunciation, memorability).
Available MCP Tools
mcp__althing__run_quick_poll— Single-question poll across personas (fastest, cheapest).mcp__althing__run_panel— Full panel run using the bundledname-testbranching instrument that probes meaning, pronounceability, or memorability based on first reactions. Its opening question has a{candidates}placeholder; fill it with thevarsargument (see Step 2).mcp__althing__list_persona_packs/mcp__althing__get_persona_pack— Reuse saved personas instead of inventing new ones.mcp__althing__list_instrument_packs— Confirm thename-testpack is available.
Workflow
Step 1: Gather Inputs
Ask for:
- The candidate names (comma-separated).
- A one-sentence description of what the product/feature does.
- Target audience (so personas are relevant).
Step 2: Choose Depth
- Quick gut check →
run_quick_pollwith a question that has the description and candidate names written directly into thequestionstring, e.g. "Which of these names best fits a budget travel app — Wander, Roamly, Tr9? Why?" - Full branching evaluation →
run_panelwithinstrument_pack="name-test"andvars={"candidates": "Name A, Name B"}— the comma-separated candidate names are substituted into the opening question's{candidates}placeholder before the panel runs. (CLI equivalent:althing panel run --instrument name-test --var 'candidates=Name A, Name B'.) If you omitvars, the call fails fast with a typedINVALID_TOOL_ARGerror naming the missing placeholder. The instrument branches into meaning-probe, pronounce-probe, or memorability-probe based on what surfaces first.
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.
- 1mo ago First seen · 63 lines · 34 tokens per session scan A a9a609fdb8b0
name-test is a skill published in the GitHub repository DataViking-Tech/Althing (2 stars, last pushed 2d ago), licensed MIT. It adds 34 tokens to every session and 893 once invoked, about $0.0001 per session on Opus 5.5. 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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