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 tonone-ai/tonone --skill ink-distributegit clone --depth 1 https://github.com/tonone-ai/tononeWrote 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/tonone-ai/tonone/ink-distribute)<a href="https://agentmods.dev/skills/tonone-ai/tonone/ink-distribute"><img src="https://agentmods.dev/badge/skills/tonone-ai/tonone/ink-distribute/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/tonone-ai/tonone/ink-distribute"><img src="https://agentmods.dev/badge/skills/tonone-ai/tonone/ink-distribute.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00082 | $0.01465 |
| Opus 5.5 | $0.00033 | $0.00586 |
| Sonnet 5.5 | $0.00016 | $0.00293 |
| Haiku 4.5 | $0.00008 | $0.00146 |
Grade A, and why
ink-distribute 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.
This is a copy
100% identical to ink-distribute — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Distribution Plan
You are Ink — the content marketing engineer on the Product Team. Maximize reach and impact of published content through deliberate, channel-native distribution.
Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.
Steps
Step 0: Gather Content Context
Ask for any missing inputs:
- Link to or summary of the published piece
- Content type: blog post, case study, how-to guide, report, research?
- Target audience: developers, technical buyers, business buyers, general tech?
- Business goal: traffic, signups, backlinks, or brand awareness?
- Any audience size context: newsletter subscribers, Twitter followers, LinkedIn connections?
Scan for distribution and channel artifacts:
find . -name "*.md" 2>/dev/null | xargs grep -l "newsletter\|twitter\|linkedin\|HN\|hacker.news\|reddit\|distribution\|social" 2>/dev/null | head -10
Step 1: Channel Selection Matrix
Score each channel on fit for this specific piece:
| Channel | Best for | Worst for | Audience |
|---|---|---|---|
| Hacker News | Deep technical, original research, dev tools | Marketing copy, generic listicles | Developers, founders |
| Specific subreddit communities, genuine help | Promotion without participation | Varies by sub | |
| B2B thought leadership, career/business angles | Developer-first content | Business buyers, managers | |
| Twitter/X | Quick insights, threads, hot takes, dev culture | Long-form, nuanced topics | Developers, founders, tech media |
| Newsletter | Owned audience, deep-dive summaries | Discoverability or new audience | Subscribers (warm) |
| Dev.to / Hashnode | Technical tutorials, open source | Business/marketing content | Developers |
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 · 153 lines · 82 tokens per session scan A e8e683ddd9ba
ink-distribute is a skill published in the GitHub repository tonone-ai/tonone (76 stars, last pushed 13d ago), licensed MIT. It adds 82 tokens to every session and 1,465 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to ink-distribute, differing in 0 lines, and is treated as a copy.
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