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/Owl-Listener/ai-design-skillsWrote 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/owl-listener/ai-design-skills/design-conversation)<a href="https://agentmods.dev/commands/owl-listener/ai-design-skills/design-conversation"><img src="https://agentmods.dev/badge/commands/owl-listener/ai-design-skills/design-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/owl-listener/ai-design-skills/design-conversation"><img src="https://agentmods.dev/badge/commands/owl-listener/ai-design-skills/design-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 | $0.00012 | $0.00429 |
| Opus 5 | $0.00006 | $0.00215 |
| Sonnet 5 | $0.00002 | $0.00086 |
| Haiku 4.5 | $0.00001 | $0.00043 |
Grade A, and why
design-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 11d 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.
What it actually says
You are designing a human-AI conversation flow. Use only skills from the model-interaction-design plugin. Follow this process:
Step 1: Understand the Task
Using conversation-patterns, identify:
- What is the user trying to accomplish?
- What information does the AI need from the user?
- What information does the user need from the AI?
- What's the expected conversation length (2 turns or 20)?
Step 2: Choose the Dialogue Structure
Using conversation-patterns, select the appropriate structure:
- Interview, co-creation, instruction-execution, exploration, or guided workflow
- Justify why this structure fits the task
Step 3: Map Initiative
Using mixed-initiative-flow, define:
- Who initiates the conversation?
- Where does initiative shift from user to AI and back?
- What triggers each handoff?
- Create an initiative map showing control at each stage
Step 4: Design Modality
Using multimodal-orchestration, specify:
- What modalities are used for input and output at each stage?
- Where do cross-modal transitions happen?
- What's the primary modality and what's supporting?
Step 5: Plan for Breakdown
Using conversation-patterns (repair sequences) and feedback-loops:
- Design 3 repair sequences for likely misunderstandings
- Define how the user corrects the AI mid-conversation
- Specify grounding checkpoints
Step 6: Design Disclosure
Using progressive-disclosure:
- What capabilities are revealed at conversation start?
- What's revealed as the conversation progresses?
- How does the AI teach the user what else it can do?
Output
Deliver a complete conversation design document:
- Conversation flow diagram (text-based) showing all turns
- Initiative map
- Modality specification per stage
- Repair protocol
- Disclosure plan
- 3 example conversation transcripts (happy path, error recovery, edge case)
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.
- 11d ago First seen · 46 lines · 12 tokens per session scan A 1e76d8bcd25d
design-conversation is a command published in the GitHub repository Owl-Listener/ai-design-skills (172 stars, last pushed 3mo ago), licensed MIT. It adds 12 tokens to every session and 429 once invoked, about $0.0001 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.
Other commands, from other repositories
profile
Save, load, inspect, update, reset, or delete diagram-design client profiles.
ui-flow-review
Review menus, HUD, navigation, and player flow from a UX perspective.
responsive-design-specialist
Use when a layout breaks between sizes. Arbitrary breakpoints, type that does not scale, images that blow out the grid, or a desktop design retrofitted onto mobile.
ppt-image2-editable-rebuild
Rebuild image2 or imagegen reference slides as editable PowerPoint decks.
p3-ux-wireframes
Creates wireframes (ASCII art) for the most important screens with interaction descriptions.
team-ui
Orchestrate UI/UX design team.