ai-ux-patterns

ai-ux-patterns is a skill for Claude Code from VandanaAjayDubey111/great-pm. It costs 84 tokens per session (3,799 once invoked), scanned A, original, MIT.

A user-experience guide for software that can produce uncertain or variable results. It covers showing confidence, handling mistakes, allowing people to undo actions, involving people in decisions, and revealing detail gradually.

In plain words
What is it for?
Use it to plan screens and interactions for AI features, including review steps, error handling, and reversible actions.
Why use it?
It helps teams design AI features that make uncertainty and failure understandable rather than treating guesses as guaranteed answers.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions Codex.

Part of the great-pm plugin — 114 skills, 34 commands, 48 agents, 5 hooks shipped together

Good fit Use it to plan screens and interactions for AI features, including review steps, error handling, and reversible actions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/vandanaajaydubey111/great-pm/ai-ux-patterns
Install

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.

Any agent
npx skills add VandanaAjayDubey111/great-pm --skill ai-ux-patterns
Clone the repo
git clone --depth 1 https://github.com/VandanaAjayDubey111/great-pm

Made for: Claude Code.

Or install great-pm, the plugin that ships this one along with the rest of its 114 skills, 34 commands, 48 agents, 5 hooks.

Wrote 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.

agentmods badge for ai-ux-patterns

README.md
[![agentmods](https://agentmods.dev/badge/skills/vandanaajaydubey111/great-pm/ai-ux-patterns/github.svg)](https://agentmods.dev/skills/vandanaajaydubey111/great-pm/ai-ux-patterns)
Your own site
<a href="https://agentmods.dev/skills/vandanaajaydubey111/great-pm/ai-ux-patterns"><img src="https://agentmods.dev/badge/skills/vandanaajaydubey111/great-pm/ai-ux-patterns/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.

agentmods 80×15 button for ai-ux-patterns

Your own site · 80×15
<a href="https://agentmods.dev/skills/vandanaajaydubey111/great-pm/ai-ux-patterns"><img src="https://agentmods.dev/badge/skills/vandanaajaydubey111/great-pm/ai-ux-patterns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 84 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,799 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00084 $0.03799
Opus 5.5 $0.00034 $0.01520
Sonnet 5.5 $0.00017 $0.00760
Haiku 4.5 $0.00008 $0.00380

Measured 1mo ago against content hash e50dfeb8dca0, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ai-ux-patterns 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.

plugins/great-pm/skills/ai-ux-patterns/SKILL.md · 321 lines

How it starts

The opening of the file, as written. The whole thing — 321 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Codex host binding

  • Treat references to Claude slash workflows as the equivalently named Codex skill.
  • Before delegating to any specialist, read the great-pm-runtime skill and the selected packaged role file.
  • Treat "invoke", "assign", "delegate", "spawn", and source Agent-tool instructions as a required Codex spawn_agent call with that role and a bounded assignment.
  • For the spawn tool's task_name or agent_name identifier, replace canonical role-name hyphens with underscores (query-refiner-pm → query_refiner_pm). Keep canonical names unchanged in prompts, filenames, verdict logs, and user-facing output; this is an internal identifier mapping, not a role rename.
  • Store every returned agent identifier. Never call a wait tool until a spawn has returned an identifier, and wait only on identifiers returned by successful spawns.
  • If spawn_agent is unavailable or a spawn fails, report BLOCKED; do not impersonate the specialist or wait on an empty agent set.
  • Resolve bundled paths from the installed GreatPM plugin root.
  • Ignore Claude-only model aliases, colors, turn limits, and tool allowlists.
  • Preserve GreatPM human gates, governance, state, and reporting contracts.

AI UX patterns — designing for non-determinism

Deterministic software gives the same output for the same input, every time. UX assumes the system is right. AI features are probabilistic: they are sometimes wrong, sometimes unsure, and sometimes slow — and the UX must be designed around that uncertainty, not in spite of it.

Google's People + AI Research (PAIR) guidebook and Apple's Human Interface Guidelines for machine learning converge on the same core: the job of AI UX is earning and calibrating trust under uncertainty. Four patterns do most of the work — confidence signals, graceful failure, reversibility, human-in-the-loop — plus progressive disclosure to keep control from becoming overwhelm.

This skill is the trust & uncertainty layer for probabilistic features. It complements hooked-ux (the habit loop for any product); it does not overlap it.

Read the full file on GitHub · 321 lines

Changes

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.

  1. 1mo ago First seen · 321 lines · 84 tokens per session scan A e50dfeb8dca0

Subscribe to this mod's changes

ai-ux-patterns is a skill published in the GitHub repository VandanaAjayDubey111/great-pm (3 stars, last pushed 1mo ago), licensed MIT. It adds 84 tokens to every session and 3,799 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-21.

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