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/datit309/supergraph/prototypenpx skills add datit309/supergraph --skill prototypegit clone --depth 1 https://github.com/datit309/supergraphWhat 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 | $0.00062 | $0.00982 |
| Opus 5 | $0.00031 | $0.00491 |
| Sonnet 5 | $0.00012 | $0.00196 |
| Haiku 4.5 | $0.00006 | $0.00098 |
Grade A, and why
prototype 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 yesterday.
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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/supergraph:prototype
Throwaway code to validate approach. Explore fast, decide, then delete or integrate.
Announce: "🧪 /supergraph:prototype — building throwaway prototype..."
When to Use
- Between
/supergraph:analyzeand/supergraph:planwhen approach is uncertain - Multiple valid UI designs need visual comparison
- Core logic (state machine, algorithm, data model) needs validation before full TDD
- User says "I'm not sure which approach" or "can we try both?"
Choose Branch
Ask user (or infer from task):
Logic branch — validate state, algorithm, or data model
UI branch — validate layout, interaction, or multiple designs
Logic Branch
Goal: validate core logic in a minimal terminal program.
Rules:
- Single file (
prototype-<slug>.ts/.py/ etc.) - No database, no HTTP, no external services — in-memory only
- No tests — feedback is the running output
- Single command to run:
npx ts-node prototype-<slug>.tsor equivalent - Hard-code sample data
Structure (TypeScript example):
// prototype-<slug>.ts — THROWAWAY, do not review
type State = "idle" | "processing" | "done" | "error"
type Event = { type: "start" } | { type: "finish" } | { type: "fail" }
function transition(state: State, event: Event): State {
// ...
}
// Run through sample cases
const cases = [ ... ]
cases.forEach(({ from, event, expected }) => {
const result = transition(from, event)
console.log(result === expected ? "✅" : "❌", { from, event, result, expected })
})
Run and observe:
npx ts-node prototype-<slug>.ts
UI Branch
Goal: compare multiple visual/interaction designs without committing.
Rules:
- All designs live on ONE route:
/prototype/<slug> - URL param
?design=A|B|Cswitches between designs - Floating control bar (fixed position) lets user switch designs visually
- No persistence layer — mock data only
- No auth, no real API calls
- Single command to start:
npm run dev(or project equivalent)
Structure:
app/prototype/<slug>/page.tsx (router + floating switcher)
app/prototype/<slug>/DesignA.tsx
app/prototype/<slug>/DesignB.tsx
app/prototype/<slug>/DesignC.tsx
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.
- yesterday First seen · 137 lines · 62 tokens per session scan A b45166b8078f
prototype is a skill published in the GitHub repository datit309/supergraph (21 stars, last pushed 4d ago), licensed MIT. It adds 62 tokens to every session and 982 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 2026-08-30.
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