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/armanzeroeight/fastagent-plugins/readme-generatornpx skills add armanzeroeight/fastagent-plugins --skill readme-generatorgit clone --depth 1 https://github.com/armanzeroeight/fastagent-pluginsWhat 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 | $0.00028 | $0.00723 |
| Opus 5 | $0.00014 | $0.00362 |
| Sonnet 5 | $0.00006 | $0.00145 |
| Haiku 4.5 | $0.00003 | $0.00072 |
Grade A, and why
readme-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 3d 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
README Generator
Quick Start
Generate a README based on project type:
# Detect project type
ls package.json && echo "Node.js project" || \
ls setup.py pyproject.toml && echo "Python project" || \
ls go.mod && echo "Go project"
Instructions
Step 1: Analyze Project
Gather project information:
- Project name (from package.json, pyproject.toml, etc.)
- Description (from manifest or git)
- Main language and framework
- Key features (scan source files)
- Dependencies (from manifest files)
Step 2: Select Template
Choose template based on project type:
| Type | Template | Key Sections |
|---|---|---|
| Library | library | Installation, API, Examples |
| CLI Tool | cli | Installation, Commands, Options |
| Web App | webapp | Features, Setup, Deployment |
| API | api | Endpoints, Authentication, Examples |
Step 3: Generate Core Sections
Title and Description:
# Project Name
Brief one-line description of what the project does.
[](LICENSE)
[](package.json)
Installation:
## Installation
\`\`\`bash
npm install project-name
# or
pip install project-name
\`\`\`
Usage:
## Usage
\`\`\`javascript
const project = require('project-name');
// Basic example
project.doSomething();
\`\`\`
Step 4: Add Project-Specific Content
Include relevant sections:
- Features: Bullet list of key capabilities
- API Reference: For libraries
- Configuration: For configurable tools
- Examples: Real-world use cases
- Contributing: How to contribute
- License: License information
Step 5: Add Badges and Links
Common badges:
What ships with it
2 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.
- 3d ago First seen · 125 lines · 28 tokens per session scan A e2270f3140c0
readme-generator is a skill published in the GitHub repository armanzeroeight/fastagent-plugins (29 stars, last pushed 1mo ago), licensed MIT. It adds 28 tokens to every session and 723 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.
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