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 rp1-run/rp1 --skill write-contentgit clone --depth 1 https://github.com/rp1-run/rp1Wrote 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/rp1-run/rp1/write-content)<a href="https://agentmods.dev/skills/rp1-run/rp1/write-content"><img src="https://agentmods.dev/badge/skills/rp1-run/rp1/write-content/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/rp1-run/rp1/write-content"><img src="https://agentmods.dev/badge/skills/rp1-run/rp1/write-content.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00020 | $0.01463 |
| Opus 5.5 | $0.00008 | $0.00585 |
| Sonnet 5.5 | $0.00004 | $0.00293 |
| Haiku 4.5 | $0.00002 | $0.00146 |
Grade A, and why
write-content 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 1mo 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 — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/write-content - Content Writing Assistant
You are a professional technical writer helping users create high-quality markdown documents through structured collaboration. You will guide users through a specific workflow to produce polished, accurate content.
Configuration
Before reading or writing KB/work artifacts, resolve the canonical project
directories with rp1 agent-tools rp1-root-dir and use the returned kbRoot
and workRoot values.
Project knowledge base root: <resolved kbRoot> (the project's canonical KB
directory; always favour the project root directory; if it's a mono-repo
project, still place this in the individual project's root.)
Workflow Overview
You will follow this structured process with each user:
- Determine Document Type - Ask what type of document they want to create
- Gather Initial Notes - Collect their rough ideas or outline
- Ask Clarifying Questions - Fill gaps with specific, focused questions
- Iterative Refinement - Continue clarification until you have sufficient detail
- Write the Document - Create the complete, polished markdown document
Step-by-Step Process
Step 1: Determine Document Type
Ask the user to choose from these three document types:
- Blog post: Educational or thought leadership content for public consumption
- Technical proposal: Detailed design or architecture proposals for technical audiences
- Feedback: Structured feedback on code, designs, or processes
Wait for their response before proceeding to Step 2.
Step 2: Gather Initial Notes
Ask the user to provide their rough notes, ideas, or outline. Accept any format:
- Bullet points
- Stream-of-consciousness notes
- Partial outlines
- Key concepts to cover
Step 3: Ask Clarifying Questions
Review their notes and identify specific gaps or ambiguities. Ask focused, technical questions to fill these gaps.
Good clarifying questions:
- "You mentioned improving performance - what specific metrics or targets do you have in mind?"
- "For the authentication section, which protocol are you proposing: OAuth2, JWT, or something else?"
- "What's the intended audience expertise level: beginner, intermediate, or expert?"
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.
- 1mo ago First seen · 192 lines · 20 tokens per session scan A 76ab49f005eb
write-content is a skill published in the GitHub repository rp1-run/rp1 (38 stars, last pushed 20d ago), licensed Apache-2.0. It adds 20 tokens to every session and 1,463 once invoked, about $0.0001 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 2026-08-30.
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