Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/PMDevSolutions/Aureliusnpx agentmods add skills/pmdevsolutions/aurelius/conversation-intakeWrote 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/pmdevsolutions/aurelius/conversation-intake)<a href="https://agentmods.dev/skills/pmdevsolutions/aurelius/conversation-intake"><img src="https://agentmods.dev/badge/skills/pmdevsolutions/aurelius/conversation-intake.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 5.1 | $0.00098 | $0.02779 |
| Opus 5 | $0.00049 | $0.01389 |
| Sonnet 5 | $0.00020 | $0.00556 |
| Haiku 4.5 | $0.00010 | $0.00278 |
Grade A, and why
conversation-intake 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 — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Conversation Intake — Structured Discovery
Purpose
Gather everything needed to design and build an app from nothing but a conversation. Where figma-intake discovers an existing design file, this skill discovers the user's intent: it interviews them (maximum of 7 questions), expands the answers into concrete design decisions via the conversation-designer agent, and outputs two machine-readable artifacts that the rest of the pipeline consumes without re-asking questions:
.claude/plans/build-spec.jsonwith"source": "conversation"— same contract every other intake skill produces.claude/plans/design-brief.json— the new artifact that drives Figma design generation in Phase C1
When to Use
- Phase C0 of
/build-from-conversation - Any time a user describes an app they want built but has no Figma/Canva file, screenshot, or URL
- When you need a structured design brief from a free-form product description
Inputs
- Optional: Initial description from
$ARGUMENTS(seed answers; skip any question it already answers) - Optional: Existing project directory to integrate into
- Reads:
.claude/pipeline.config.json→conversation.interview(maxQuestions,confirmBriefWithUser)
Process
Step 1: Auto-Discovery (No User Input)
Scan the local project exactly as the other intake skills do:
1. Detect framework via the renderer registry:
- Run: node scripts/renderer-registry.js detect . --json
- On { "renderer": "<name>", "language": "<lang>" }:
set build-spec renderer = <name>
set build-spec outputTarget = <language> (react | vue | svelte | react-native)
- On { "renderer": null }:
no framework detected → ask the output-target question (Question 5)
Do not hand-sniff config files or package.json deps; the registry owns detection.
2. Detect app type:
- manifest.json with "manifest_version" → Chrome Extension
- manifest.json with "start_url" or "display" → PWA
- Otherwise → Web App
3. Scan existing components:
- Glob: src/components/**/*.tsx, app/components/**/*.tsx
- Build inventory: name, props interface, file path
- (Only triggers Question 7 if matches exist)
4. Check package.json for UI libraries and state management
(same list as figma-intake)
5. Check for existing design tokens:
- tailwind.config.ts theme.extend, src/styles/tokens.css,
design-tokens.lock.json (from prior runs)
- Existing tokens become constraints for the design brief, not questions
6. Load pipeline config:
- .claude/pipeline.config.json → conversation.interview.maxQuestions (default 7)
and appTypes[detected] for E2E strategy defaults
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 · 232 lines · 0 tokens per session scan A a2179eba66f2
conversation-intake is a skill published in the GitHub repository PMDevSolutions/Aurelius (8 stars, last pushed 21d ago), licensed MIT. It adds 98 tokens to every session and 2,779 once invoked, about $0.0005 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 2026-09-04.
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