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.
git clone --depth 1 https://github.com/PMDevSolutions/AureliusWrote 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/commands/pmdevsolutions/aurelius/build-from-conversation)<a href="https://agentmods.dev/commands/pmdevsolutions/aurelius/build-from-conversation"><img src="https://agentmods.dev/badge/commands/pmdevsolutions/aurelius/build-from-conversation/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/commands/pmdevsolutions/aurelius/build-from-conversation"><img src="https://agentmods.dev/badge/commands/pmdevsolutions/aurelius/build-from-conversation.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 | $0.00000 | $0.01836 |
| Opus 5.5 | $0.00000 | $0.00734 |
| Sonnet 5.5 | $0.00000 | $0.00367 |
| Haiku 4.5 | $0.00000 | $0.00184 |
Grade A, and why
build-from-conversation 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/build-from-conversation — Conversational App Creation via Figma Generation
You are the master orchestrator for building a working, tested app from nothing but a conversation. The user describes what they want; you interview them, generate a real Figma design from the resulting brief, and then hand off to the existing /build-from-figma pipeline, which runs unchanged from there. "Talk to build" — no pre-existing design file required.
Conversation ──► [C0] conversation-intake ──► build-spec.json + design-brief.json
│
▼
[C1] design-brief-to-figma ──► real Figma file (URL + node IDs)
│
▼
/build-from-figma <generated URL> ──► phases 0-9, unchanged
Key enforcement rules:
- The interview is bounded — at most
conversation.interview.maxQuestions(default 7) questions. Auto-discover everything else. - The brief is confirmed — when
conversation.interview.confirmBriefWithUseristrue, the user approves the build plan before any Figma file is created. - The generated design is reviewed — when
conversation.designGeneration.reviewBeforeHandoffistrue, the user sees the Figma file before the build pipeline starts. - Downstream is untouched — everything after the handoff is the standard
/build-from-figmapipeline; this command adds phases in front of it, never modifies it.
Input
The user provides: $ARGUMENTS (optional — a brief initial description of the app, e.g. "a minimal analytics dashboard with auth and dark mode")
If $ARGUMENTS is non-empty, pass it to the conversation-intake skill as seed answers; the skill skips any interview question the description already answers. If empty, the interview starts from Question 1.
Configuration
Load .claude/pipeline.config.json at the start. This command reads the conversation section:
conversation.interview— question cap, brief confirmation gateconversation.designGeneration— mockup directory and server port, capture polling, review gate, regeneration attemptsconversation.retry— exponential backoff for Figma MCP capture failures
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 · 115 lines · 0 tokens per session scan A a64c2bf48b91
build-from-conversation is a command published in the GitHub repository PMDevSolutions/Aurelius (9 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,836 tokens. 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 2026-09-04.
Other commands, from other repositories
figma-start
A command that prepares a designer's review branch from a developer's GitHub pull request. A pull request is a proposed set of code changes, and a branch is a separate line of project history.
figma-apply
A command that applies changes from a Figma design file to the current design branch, then commits, pushes, and checks the project build. Figma is a tool for creating and sharing interface designs.
design-tutorial
Interactive guided tour of Naksha — learn commands through real exercises, discover workflows, and get oriented in under 10 minutes.
figma-component-library
Generate a complete component library in Figma from a design system config — atoms, molecules, and organisms with all variants, auto layout, and component properties.
print-audit
Audit a print layout for bleed, safe zone, color mode, font embedding, and page break rules. Optionally audits brand consistency when brand context is provided.
dashboard-layout
Design and build a complete dashboard layout — sidebar navigation, KPI cards, chart areas, data tables, filter bar, and responsive behavior. Outputs production-ready HTML/CSS.