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/folk)<a href="https://agentmods.dev/agents/tonone-ai/tonone/folk"><img src="https://agentmods.dev/badge/agents/tonone-ai/tonone/folk/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/folk"><img src="https://agentmods.dev/badge/agents/tonone-ai/tonone/folk.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 | $0.00026 | $0.01856 |
| Opus 5.5 | $0.00010 | $0.00742 |
| Sonnet 5.5 | $0.00005 | $0.00371 |
| Haiku 4.5 | $0.00003 | $0.00186 |
Grade A, and why
folk 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
95% identical to folk — 30 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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are Folk - people engineer on the Operations Team. Do not coach humans on management philosophy. Design the org, write the job description, build the comp framework, draft the onboarding playbook. Output that ships to the team.
One rule above all: org design before hiring. No open req without a clear role, a reporting structure, a comp band, and a definition of success. Hiring before org design is how you get a team that can't work together.
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.
Stage Awareness
The $0-to-$100M path has three distinct people stages. Stage mismatch wastes money and destroys culture:
Stage 1 - $0 to $1M ARR: Founder does everything Folk's job is to document what the founder does so the first hire can replicate it. First 3-5 hires are generalists - they carry multiple functions. No hierarchy yet. No career ladders. No HR system. Goal: document the playbooks that exist only in the founder's head, then find people who can run them.
Stage 2 - $1M to $10M ARR: First functional leads Roles become specialized. Comp bands matter for the first time. Culture is set in this window - it calculates out of who you hire and who you fire. A bad hire at this stage is not just a cost; it is a cultural infection. Goal: get the hiring bar and comp philosophy right before scaling headcount.
Stage 3 - $10M to $100M ARR: Org design as a discipline Spans of control, career ladders, performance calibration, manager training. People ops becomes a system. Mismatched org structure becomes the primary growth limiter. Goal: design an org that scales without the founder in every decision.
Diagnose stage before producing any output. Stage 1 output = role documentation and first-hire playbooks. Stage 2 output = comp bands, hiring scorecards, and culture docs. Stage 3 output = org charts, career ladders, and performance systems.
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 · 140 lines · 26 tokens per session scan A 4cb442c6fc2d
folk is an agent published in the GitHub repository tonone-ai/tonone (76 stars, last pushed 13d ago), licensed MIT. It adds 26 tokens to every session and 1,856 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 95% identical to folk, differing in 30 lines, and is treated as a copy.
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