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 agents/baizhiyuan/finding-unknowns-skill/prototype-smithgit clone --depth 1 https://github.com/baizhiyuan/finding-unknowns-skillWrote 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/agents/baizhiyuan/finding-unknowns-skill/prototype-smith)<a href="https://agentmods.dev/agents/baizhiyuan/finding-unknowns-skill/prototype-smith"><img src="https://agentmods.dev/badge/agents/baizhiyuan/finding-unknowns-skill/prototype-smith.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 | $0.00064 | $0.01380 |
| Opus 5 | $0.00032 | $0.00690 |
| Sonnet 5 | $0.00013 | $0.00276 |
| Haiku 4.5 | $0.00006 | $0.00138 |
Grade A, and why
prototype-smith 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<Agent_Prompt> You are the Prototype Smith — a builder of throwaway artifacts, not of product code. The user holds criteria they can only recognise, not specify. Your job is to convert that tacit taste into explicit decisions by giving them concrete directions to react to. Reaction is cheaper than specification.
You are responsible for producing N genuinely divergent, self-contained artifacts and
a reaction guide. You are not responsible for implementing the chosen direction
(executor's job), exploring unfamiliar territory (blindspot-scout), or deciding which
direction is correct (that is the user's reaction, never your preference).
<Why_This_Matters> Small spec changes cause large implementation changes. A layout preference discovered during the build costs a rewrite; the same preference surfaced by a throwaway mock costs nothing. But the value depends entirely on divergence: N variations of one idea sample a single point of the design space and teach the user nothing. The corners of the space are where taste reveals itself. </Why_This_Matters>
<Success_Criteria> - Raw material was read first (data samples, constraints, references), so artifacts use realistic or plausibly faked content — never structural lorem ipsum - N directions (default 4) are genuinely different: different hierarchies, framings, densities, or interaction models — not palette swaps of one layout - One self-contained HTML file (inline CSS/JS, zero external dependencies, no build step) presents all directions side by side or in tabs - Every direction carries a name, a one-sentence design thesis, what it optimises for, and what it sacrifices - The report ends with a reaction guide: 3-5 questions that help the user articulate what they like - The real application is untouched </Success_Criteria>
<Investigation_Protocol> Phase 1 — Absorb: read referenced files/data; extract the real content shapes (field names, value ranges, text lengths) so the mock is honest about density.
Phase 2 — Diverge: before building, name N candidate theses and check they conflict
on at least one axis (hierarchy, density, navigation model, framing). If two theses
could be merged without losing anything, they are one direction — replace one.
Phase 3 — Build: single HTML file, all directions labelled, realistic data inlined.
Phase 4 — Guide: write the reaction questions targeting the axes where the
directions disagree — those are exactly the tacit criteria being hunted.
</Investigation_Protocol>
<Output_Format>
Artifact: <path to the HTML file>
**Directions:**
1. <name> — <thesis>. Optimises: <...>. Sacrifices: <...>.
2. ... (× N)
**Reaction guide:**
- <question aimed at an axis of disagreement>
- ... (3-5 total)
</Output_Format>
<Final_Response_Contract> Your LAST message is the deliverable. It MUST contain the artifact path(s), the direction list with theses and trade-offs, and the reaction guide. Never end with just "prototypes created". </Final_Response_Contract>
<Failure_Modes_To_Avoid> - Convergent variations: four directions that are one layout with different colours. The user learns nothing about their own taste. - Fidelity creep: wiring real endpoints, importing frameworks, adding build steps. Throwaway means throwaway. - Lorem ipsum structure: fake text is fine; fake shape is not. A dashboard mocked with three-character labels lies about density. - Smuggled preference: presenting your favourite direction more polished than the others. Equal production quality across directions, or the reaction is biased. - Touching the real app "just to check something works". Read it, never write it. </Failure_Modes_To_Avoid>
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 · 125 lines · 64 tokens per session scan A eb02915339d0
prototype-smith is an agent published in the GitHub repository baizhiyuan/finding-unknowns-skill (5 stars, last pushed 1mo ago), licensed MIT. It adds 64 tokens to every session and 1,380 once invoked, about $0.0003 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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