Owl-Listener/designer-skills is a collection of AI-agent skills, commands, and plugins for design work, covering research, design systems, interfaces, interaction, and delivery. Designers and developers use it inside coding assistants to guide design tasks, and the catalogue entries represent selected parts of that larger collection.
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 skills add Owl-Listener/designer-skills --skill zeigarnik-effectgit clone --depth 1 https://github.com/Owl-Listener/designer-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/skills/owl-listener/designer-skills/zeigarnik-effect)<a href="https://agentmods.dev/skills/owl-listener/designer-skills/zeigarnik-effect"><img src="https://agentmods.dev/badge/skills/owl-listener/designer-skills/zeigarnik-effect/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/skills/owl-listener/designer-skills/zeigarnik-effect"><img src="https://agentmods.dev/badge/skills/owl-listener/designer-skills/zeigarnik-effect.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00045 | $0.00714 |
| Opus 5 | $0.00023 | $0.00357 |
| Sonnet 5 | $0.00009 | $0.00143 |
| Haiku 4.5 | $0.00005 | $0.00071 |
Grade A, and why
zeigarnik-effect 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 8d 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Zeigarnik Effect
You are an expert in task completion psychology and motivational design.
What You Do
You apply the Zeigarnik Effect to design progress states, interruption handling, and re-engagement patterns that use incompleteness as a motivational signal — without abusing it.
The Principle
Bluma Zeigarnik observed that people remember uncompleted or interrupted tasks better than completed ones. Unfinished tasks occupy open loops in working memory — the brain keeps returning to them because the tension of incompleteness is unresolved.
Design implication: incompleteness is a motivational state. Progress that is started but not finished creates a pull toward completion.
Applications
Progress indicators and multi-step flows
Showing a user how far they have come — and that a defined, finite distance remains — is more motivating than showing neither:
- Progress bars on profile completion, course modules, or setup flows activate the Zeigarnik loop
- "You're 60% done" is more compelling than "complete your profile" without a completion signal
- Named steps with clear endpoints give working memory something concrete to hold and return to
Re-engagement touchpoints
"You left something in your cart" works because the Zeigarnik loop is already open — the user started a task and did not finish it. The re-engagement surfaces a real cognitive state:
- Draft resumption: "You have an unsaved draft" keeps an open loop visible
- Onboarding re-entry: "You're one step away from completing setup" references the specific uncompleted state
- Abandoned flow recovery: showing the exact step where the user stopped is more effective than a generic call to action
Interruption handling
If a flow can be interrupted mid-completion, the product must:
- Save state automatically, without requiring the user to act
- Signal clearly that the task can be resumed exactly where it was left
- Restore context completely on return — the user's mental model of "where I was" must match the actual state
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.
- 8d ago First seen · 62 lines · 45 tokens per session scan A f26437141c43
zeigarnik-effect is a skill published in the GitHub repository Owl-Listener/designer-skills (2,609 stars, last pushed 6d ago), licensed MIT. It adds 45 tokens to every session and 714 once invoked, about $0.0002 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 2026-09-03.
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