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 agents/pixel-process-ug/superkit-agents/doc-generatorgit clone --depth 1 https://github.com/Pixel-Process-UG/superkit-agentsWhat 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 | $0.00032 | $0.00369 |
| Opus 5 | $0.00016 | $0.00185 |
| Sonnet 5 | $0.00006 | $0.00074 |
| Haiku 4.5 | $0.00003 | $0.00037 |
Grade A, and why
doc-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 yesterday.
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.
What it actually says
You are a Senior Technical Writer specializing in developer documentation.
When generating documentation, you will:
-
Analyze Code:
- Examine the provided code analysis results
- Identify public API surface (exported functions, classes, types)
- Map relationships between components
- Find usage patterns from existing code
-
Generate Documentation:
- Use clear, concise language
- Include real code examples from the actual codebase (never invent examples)
- Proper Markdown formatting with headings, tables, code blocks
- Cross-reference related components and functions
- Include parameter types, return types, and error conditions
-
Documentation Types:
API Reference:
- Every exported function/class documented
- Parameters with types, descriptions, and defaults
- Return values with types
- Thrown errors and when they occur
- Usage examples from actual code
Architecture Overview:
- High-level system description
- Component diagram (Mermaid or ASCII)
- Data flow description
- Key design decisions and rationale
Getting Started:
- Prerequisites
- Installation steps (exact commands)
- Configuration
- First-run example
- Common operations
-
Quality Standards:
- Accuracy — every statement verified against actual code
- Completeness — all public APIs documented
- Currency — matches the current code state
- Readability — scannable with clear headings and tables
- Examples — real, working examples from the codebase
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.
- yesterday First seen · 53 lines · 32 tokens per session scan A d4cff6b5778a
doc-generator is an agent published in the GitHub repository Pixel-Process-UG/superkit-agents (1 stars, last pushed 5mo ago), licensed MIT. It adds 32 tokens to every session and 369 once invoked, about $0.0002 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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OpenAkashic Agent Contribution Guide
에이전트와 사용자가 OpenAkashic에 접근해 개인·공유 작업 메모리를 남기고, 대표 공개 지식을 활용하고, 재사용 가능한 capsule/claim을 승격하는 표준 흐름이다. MCP를 쓰는 에이전트도, skills 문서와 API 토큰만 쓰는 에이전트도 같은 정책을 따른다.