PM Skills is a collection of plain-Markdown instructions that teach AI assistants structured methods for handling professional, personal, and life-admin tasks. People use it with Claude, ChatGPT, Gemini, Cursor, Codex, and other supported agents for work such as writing product requirements, reviewing documents, or planning difficult situations.
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 mohitagw15856/pm-claude-skills --skill explorer-viewer-buildergit clone --depth 1 https://github.com/mohitagw15856/pm-claude-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/mohitagw15856/pm-claude-skills/explorer-viewer-builder)<a href="https://agentmods.dev/skills/mohitagw15856/pm-claude-skills/explorer-viewer-builder"><img src="https://agentmods.dev/badge/skills/mohitagw15856/pm-claude-skills/explorer-viewer-builder/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/mohitagw15856/pm-claude-skills/explorer-viewer-builder"><img src="https://agentmods.dev/badge/skills/mohitagw15856/pm-claude-skills/explorer-viewer-builder.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 | $0.00104 | $0.01049 |
| Opus 5.5 | $0.00042 | $0.00420 |
| Sonnet 5.5 | $0.00021 | $0.00210 |
| Haiku 4.5 | $0.00010 | $0.00105 |
Grade A, and why
explorer-viewer-builder 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 4d 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Explorer Viewer Builder
The last step of a 3D explorer is a page anyone can open: no install, no build step, works on a phone. This skill produces a single HTML file from the tested template in references/viewer-template.html: Three.js from a CDN, a GLB loader, orbit controls, clickable parts with sourced labels, an exploded view and a quiz mode, filled in with the parts list and palette from the earlier steps.
Required Inputs
Ask for these if not provided:
- The GLB file (path or URL), or confirmation to start with the template's demo assembly
- The parts list: mesh name, label, description and source for each part (from model-prompt-pack)
- Palette and layout values (from explorer-interface-brief), or accept the template defaults
- Title and the illustrative statement
- Hosting: GitHub Pages, a static host, or opening the file locally (GLB files need a local server; browsers block
file://loading)
Output Structure
1. The viewer file
A complete index.html based on the template, with:
- CONFIG filled in:
title,model, andparts(one entry per mesh name, each withlabel,descriptionandsource) - Palette applied to the CSS custom properties, with a dark-mode block
- The illustrative statement in the panel footer
- unchanged core behaviour from the template: orbit controls with damping; click (or tap) to select, ignoring drags; selection through the parts list for keyboard users; exploded view that moves each part away from the model's centre in its parent's space; quiz mode that asks for a random part, scores answers and highlights the right part after a miss; reset view; a demo fallback and a console warning if the model fails to load; a list of the model's mesh names when none match the parts list
2. Mesh-name check
A table matching the parts list against the mesh names the viewer reports (open the page with the model and read the panel, or the console): | Mesh name in parts list | Found in GLB? | Action |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 65 lines · 104 tokens per session scan A 5d3a939c095c
explorer-viewer-builder is a skill published in the GitHub repository mohitagw15856/pm-claude-skills (1,463 stars, last pushed yesterday), licensed MIT. It adds 104 tokens to every session and 1,049 once invoked, about $0.0004 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 2026-10-12.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…