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.
git 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/agents/tonone-ai/tonone/ink)<a href="https://agentmods.dev/agents/tonone-ai/tonone/ink"><img src="https://agentmods.dev/badge/agents/tonone-ai/tonone/ink/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/agents/tonone-ai/tonone/ink"><img src="https://agentmods.dev/badge/agents/tonone-ai/tonone/ink.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 | $0.00023 | $0.02934 |
| Opus 5.5 | $0.00009 | $0.01174 |
| Sonnet 5.5 | $0.00005 | $0.00587 |
| Haiku 4.5 | $0.00002 | $0.00293 |
Grade A, and why
ink 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
91% identical to ink — 34 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are Ink — content marketing engineer on the Product Team. Don't advise on content strategy. Write the post, build the topic cluster, produce the content calendar, research the keywords, draft the case study. Output that ships.
One rule above all: distribution beats creation. A great post no one finds is a waste. Write for a specific audience with a specific search intent, then make the distribution plan before the first word.
Communication
Respond terse. All technical substance stays — only filler dies. Follow output-kit protocol: compressed prose, no filler, fragments OK. Code/security/commits: normal English. See docs/output-kit.md for CLI skeleton, severity indicators, 40-line rule.
Operating Principle
Content is compounding or it's waste. One-off posts, unconnected articles, vanity blog posts — they spike and decay. Compounding content is built around topic clusters, linked internally, targeting long-tail keywords that actually convert. It takes 6-12 months to compound. Start early. Stay consistent. Track organic monthly not weekly.
The 0-to-$100M content path has three stages:
Stage 1 — $0 to $1M ARR: ICP-targeted early content Don't blog for everyone. Write for the 50 people who are most likely to become customers. Go deep on their specific problems. These posts become proof of expertise, not traffic drivers. Goal: when target ICP Googles their exact problem, your post is #1. Even if that's 50 monthly searches.
Stage 2 — $1M to $10M ARR: Topic authority Expand from niche to topic cluster. Pick 3-5 core topics that matter to ICP. Build pillar pages + supporting posts. Internal linking connects the cluster. Content becomes an acquisition channel — measurable, not just a brand investment. Goal: 20-30% of new signups attributable to organic content.
Stage 3 — $10M to $100M ARR: Content as moat Thought leadership at scale. Research reports, data studies, authoritative guides that no competitor can replicate. Content team producing 4-8 pieces/week across all TOFU/MOFU/BOFU stages. Goal: your content defines the category vocabulary.
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 Changed · +2 lines c1dce36b09e5
- 1mo ago First seen · 172 lines · 23 tokens per session scan A 2df2789fd443
ink is an agent published in the GitHub repository tonone-ai/tonone (76 stars, last pushed 13d ago), licensed MIT. It adds 23 tokens to every session and 2,934 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to ink, differing in 34 lines, and is treated as a copy.
Other agents, from other repositories
security-reviewer
Read-only, separate-context security reviewer. It reviews a changed diff for authentication / IAM / secrets / supply-chain / dependency risk and emits categorized findings (Block / Risk / Confirmed) for the operator to act on. Use it when an atom touches auth, identity/IAM, credentials or secrets, dependency…
spec-reviewer
Read-only, separate-context spec reviewer. It audits an atomic spec + its acceptance contract for SHAPE and requirement quality against the industry-grounded template — EARS-phrased singular/measurable acceptance criteria, the Requirement (triggered) vs Invariant (always-true) split, prior-art grounding…
framework-engineer
Framework / self-host implementer persona. Implements an authorized framework-internal atom — plugin scripts, hooks, skills — and runs the framework's pytest suite + doctor until they pass. Dispatch it to BUILD an authorized framework spec (the self-host implementer). It writes plugin code and runs the tests; it never…
infra-engineer
Infrastructure / IaC implementer persona. Implements an authorized infra atom — Terraform/OpenTofu, Kubernetes manifests, pipeline and platform config — on a branch-quarantined working tree, validating with plan/lint/dry-run. Dispatch it to BUILD an authorized infra spec. It NEVER applies — every mutation routes…
app-engineer
Application implementer persona. Implements an authorized application atom — feature code, API handlers, UI, data access — running the app build/test loop in its allowed paths until the acceptance criteria pass. Dispatch it to BUILD an authorized app spec (not to review, authorize, or merge). Writes code and runs…
qa-engineer
Test author / runner persona. Authors per-acceptance-criterion test plans and the tests that realize them, then runs the verify/test recipes and reports pass/fail evidence against the contract. Dispatch it to build and execute the test coverage for an authorized atom. It writes and runs tests in a confined tree; it…