Litho is a Rust-based AI documentation generator that analyzes a codebase and produces architecture documentation in the C4 model format. Developers, architects, and technical leads use it to create and maintain diagrams and code-level documentation, while the catalogue provides skills for working with the project.
Borrowing it
Nothing to install: this file belongs to sopaco/deepwiki-rs. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/sopaco/deepwiki-rs/main/.agents/skills/ai-context-generator/SKILL.mdgit clone --depth 1 https://github.com/sopaco/deepwiki-rsWrote 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/sopaco/deepwiki-rs/ai-context-generator)<a href="https://agentmods.dev/skills/sopaco/deepwiki-rs/ai-context-generator"><img src="https://agentmods.dev/badge/skills/sopaco/deepwiki-rs/ai-context-generator.svg" alt="Measured on agentmods" height="20"></a>- 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 | $0.00071 | $0.01516 |
| Opus 5 | $0.00036 | $0.00758 |
| Sonnet 5 | $0.00014 | $0.00303 |
| Haiku 4.5 | $0.00007 | $0.00152 |
Grade A, and why
ai-context-generator 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 — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Context Generator
A reusable skill for creating project knowledge bases that help coding agents work faster and smarter.
🎯 When to Use This Skill
Activate when:
- Setting up a new project for AI-assisted development
- User requests: "create ai-context", "setup project knowledge", "generate .ai-context"
- Existing
.ai-contextis outdated and needs regeneration - After major project restructuring
Do NOT activate when:
- Project already has fresh
.ai-context(checkSKILL.mddate) - User asks for unrelated documentation
- Simple code tasks with clear existing context
📋 What This Skill Generates
Creates a .ai-context/ directory with:
.ai-context/
├── SKILL.md # Entry point with activation rules
├── DYNAMICS.md # Active issues & constraints (Dynamic)
├── references/
│ ├── PROJECT-ESSENCE.md # What & why (High stability)
│ ├── ARCHITECTURE.md # Component relationships (Medium stability)
│ └── DECISIONS.md # Design decisions (Update on change)
└── meta/
├── MAINTENANCE.md # How to maintain this knowledge
├── templates/ # (Optional) Custom templates
└── scripts/ # (Optional) Maintenance scripts
Stability Tiers
| Tier | File | Update Frequency | Token Budget |
|---|---|---|---|
| 0 | PROJECT-ESSENCE.md | Quarterly / Major version | ~500 tokens |
| 1 | ARCHITECTURE.md | Monthly / Sprint | ~1000 tokens |
| 2 | DECISIONS.md | Per decision change | ~800 tokens |
| 3 | DYNAMICS.md | As needed (issues) | ~600 tokens |
🔧 Generation Process
Step 1: Gather Project Intelligence
Before generating, collect:
□ Read AGENTS.md (if exists) — operational rules
□ Read README.md — user-facing description
□ Read package.json — dependencies, scripts, entry points
□ Scan directory structure — identify components
□ Read docs/ or litho.docs/ — existing documentation
□ Identify key source files — main entry points
□ Note technology stack — frameworks, languages, platforms
What ships with it
9 files 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.
- 8d ago First seen · 216 lines · 71 tokens per session scan A 855e31e31bc7
ai-context-generator is a skill published in the GitHub repository sopaco/deepwiki-rs (1,714 stars, last pushed 24d ago), licensed MIT. It adds 71 tokens to every session and 1,516 once invoked, about $0.0004 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.
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