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 agentmods add skills/cxcscmu/skilllearnbench/technical-illustration-designnpx skills add cxcscmu/SkillLearnBench --skill technical-illustration-designgit clone --depth 1 https://github.com/cxcscmu/SkillLearnBenchWrote 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/cxcscmu/skilllearnbench/technical-illustration-design)<a href="https://agentmods.dev/skills/cxcscmu/skilllearnbench/technical-illustration-design"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/technical-illustration-design.svg" alt="Measured on agentmods" 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 | $0.00021 | $0.01222 |
| Opus 5 | $0.00010 | $0.00611 |
| Sonnet 5 | $0.00004 | $0.00244 |
| Haiku 4.5 | $0.00002 | $0.00122 |
Grade A, and why
technical-illustration-design 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 6d 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 — 176 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Technical Illustration & Exploded-View Design
Exploded-View Fundamentals
Purpose
An exploded-view diagram shows how a product is assembled by separating and offsetting each component along a central axis, revealing internal structure and layers.
Key Design Elements
-
Layering Strategy
- Arrange components vertically or along a diagonal axis
- Each layer shows a distinct component or assembly
- Maintain consistent spacing between layers
- Typically 3-7 layers for clarity
-
Assembly Axis
- Define clear direction: vertical (top-down), diagonal (45°), or horizontal
- All components should follow this axis consistently
- Creates visual harmony and understanding of assembly order
-
Component Highlighting
- Use color coding to distinguish different component types
- Each layer should be visually distinct
- Maintain color consistency throughout poster
Five Essential Hardware Layers
For the Nova device example:
-
Casing/Enclosure (Outermost)
- Outer protective shell
- Color: Corporate Dark
- Style: Solid, structured, geometric
-
Thermal Management Unit
- Heat dissipation fins or thermal pads
- Color: Secondary Brand Accent
- Shows cooling capability
- Geometric, modern appearance
-
PCB (Printed Circuit Board)
- Main electronics substrate
- Color: Tertiary Brand Accent
- Smaller, intricate details
- Shows circuit layout
-
Battery/Power System
- Energy storage component
- Color: Primary Brand Accent or Secondary
- Rectangular or cylindrical shape
- Often positioned prominently
-
Interface Connectors (Innermost/Integrated)
- Ports, connectors, user interface elements
- Color: Primary Brand Accent
- Highlight with annotation lines
- Shows connectivity
Visual Hierarchy
Title & Headers
- Primary Title: Large, bold, left-aligned or centered
- Font: Bold sans-serif (Inter, DejaVuSans)
- Color: Corporate Dark
- Size: 48-72px
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.
- 6d ago First seen · 176 lines · 21 tokens per session scan A 580d6bd83d6c
technical-illustration-design is a skill published in the GitHub repository cxcscmu/SkillLearnBench (83 stars, last pushed 1mo ago), licensed MIT. It adds 21 tokens to every session and 1,222 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 skills, from other repositories
ceo-setup
One-time onboarding for the executive/manager commitment workflow — delegation-heavy, meeting prep, decision capture, morning and evening digests. Creates a commitments project and installs two dashboard widgets. After successful setup this skill is excluded from selection until the marker file is deleted.
content-creator-setup
One-time onboarding for the content creator workflow — content pipeline stages, trend expiration, cross-platform cascades, heavy idea parking. After successful setup this skill is excluded from selection until the marker file is deleted.
github
GitHub API integration via HTTP tool with automatic credential injection.
idea-parking
Park interesting ideas for later consideration, resurface them periodically, and promote to commitments when ready.
agentsop-conventions-pinning
SOP for writing, loading, and evolving a project-level convention file (CONVENTIONS.md / CLAUDE.md / .cursor/rules / .clinerules / AGENTS.md) so that a coder-agent reliably respects your codebase's style choices every session. Tool-agnostic; covers the four load mechanics (read-only attachment, ancestor-walk…
agentsop-llamaindex
Operating-system distillation of LlamaIndex — the leading RAG / document-agent framework. Activate when the calling agent must build, debug, harden, or evaluate a Retrieval-Augmented Generation pipeline over unstructured/private data, decide between RAG primitives (Index types, retrievers, query engines, routers…