visual-discovery

visual-discovery is an agent for Claude Code from konveyor-ecosystem/playpen-pf-mig-skills. It costs 26 tokens per session (1,582 once invoked), scanned A, original, Apache-2.0.

An agent that finds the pages, routes, interface elements, and important states in a software project. It creates a manifest, which is a complete checklist for taking screenshots.

In plain words
What is it for?
Use it to inspect routing, page folders, navigation links, dynamic routes, themes, layouts, and other interface states, then prepare a manifest for visual regression testing.
Why use it?
Visual testing can miss regressions when a page or state is forgotten. A route and element inventory makes the screenshot coverage explicit before comparisons begin.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: mentions Claude Code; mentions Gemini CLI.

Good fit Use it to inspect routing, page folders, navigation links, dynamic routes, themes, layouts, and other interface states, then prepare a manifest for visual regression testing.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/konveyor-ecosystem/playpen-pf-mig-skills/visual-discovery
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.

Clone the repo
git clone --depth 1 https://github.com/konveyor-ecosystem/playpen-pf-mig-skills

Made for: Claude Code.

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 visual-discovery

README.md
[![agentmods](https://agentmods.dev/badge/agents/konveyor-ecosystem/playpen-pf-mig-skills/visual-discovery/github.svg)](https://agentmods.dev/agents/konveyor-ecosystem/playpen-pf-mig-skills/visual-discovery)
Your own site
<a href="https://agentmods.dev/agents/konveyor-ecosystem/playpen-pf-mig-skills/visual-discovery"><img src="https://agentmods.dev/badge/agents/konveyor-ecosystem/playpen-pf-mig-skills/visual-discovery/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 visual-discovery

Your own site · 80×15
<a href="https://agentmods.dev/agents/konveyor-ecosystem/playpen-pf-mig-skills/visual-discovery"><img src="https://agentmods.dev/badge/agents/konveyor-ecosystem/playpen-pf-mig-skills/visual-discovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 26 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,582 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 $0.00026 $0.01582
Opus 5 $0.00013 $0.00791
Sonnet 5 $0.00005 $0.00316
Haiku 4.5 $0.00003 $0.00158

Measured 11d ago against content hash 6e6dd516dcbb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

visual-discovery 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.

agents/visual-discovery.md · 164 lines

How it starts

The opening of the file, as written. The whole thing — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Visual Discovery

Discover every UI element and important state in a project. Produce a manifest for visual regression testing.

Inputs

  • Work directory: workspace root (manifest.md will be created here)
  • Project path: path to the project source code

Ground Rules

  • Every navigable route must appear in the manifest. If a URL is reachable by the user, it must be listed.
  • When in doubt, include it. A redundant entry is harmless. A missing entry means a regression goes undetected.
  • Do not create combinatorial entries. Capture each route once in its default state. Capture theme and layout variants only on one representative page. Do not cross-product every route with every variant.

Process

1. Discover Routes and Pages

Search the codebase for every navigable path:

  • Router config: search for route arrays, path definitions, route objects, <Route> elements
  • Page directories: check pages/, views/, routes/, screens/, app/ folders
  • Navigation elements: find menus, sidebars, navbars, breadcrumbs, footer links and extract all link targets
  • Dynamic routes: identify parameterized routes (e.g., /users/:id) and note what sample data is needed to render them

Do not stop after finding the router config. Cross-reference with navigation components to catch routes that exist in menus but not in the router (and vice versa).

Each route gets one manifest entry in its default state.

2. Discover Interactive Components

Find important components that reveal distinct UI when triggered. Group similar instances and pick one representative per type — if an app has 5 modals that all use the same Modal component with different form fields, capture one. A visual regression in the shared component will show up in any instance.

  • Modals/Dialogs — find all modals, then group by visual structure. Capture one representative per distinct layout (e.g., one form modal, one confirmation modal). Do not capture every individual "Add Credential: Network", "Add Credential: Satellite", etc. separately if they share the same modal component with different fields.
  • Drawers/Sidepanels — one representative if they share a component
  • Dropdown menus — capture one representative per distinct type (e.g., one action menu kebab, one type selector dropdown). Do not capture every individual kebab menu on every page.
  • Forms — one representative if multiple forms share the same layout
  • Tabs — only if tab panels have visually distinct structure (not just different data)
  • Wizards/Steppers — one representative step if steps share the same layout

Read the full file on GitHub · 164 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. 11d ago First seen · 164 lines · 26 tokens per session scan A 6e6dd516dcbb

Subscribe to this mod's changes

visual-discovery is an agent published in the GitHub repository konveyor-ecosystem/playpen-pf-mig-skills (2 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 26 tokens to every session and 1,582 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 2026-08-31.

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