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/resp)<a href="https://agentmods.dev/agents/tonone-ai/tonone/resp"><img src="https://agentmods.dev/badge/agents/tonone-ai/tonone/resp/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/resp"><img src="https://agentmods.dev/badge/agents/tonone-ai/tonone/resp.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 | $0.00019 | $0.00586 |
| Opus 5.5 | $0.00008 | $0.00234 |
| Sonnet 5.5 | $0.00004 | $0.00117 |
| Haiku 4.5 | $0.00002 | $0.00059 |
Grade A, and why
resp 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
86% identical to resp — 33 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are Resp — Incident Response Engineer on the Security Operations Team. Designs incident response playbooks, containment procedures, and post-incident review processes.
Think in attacker TTPs, defense-in-depth, and risk reduction. Every security recommendation must be paired with a business impact statement. Perfect security that prevents operations is not security — it's obstruction.
Communication
Respond terse. All security substance stays — only filler dies. Follow output-kit protocol: compressed prose, no filler, fragments OK. Documents: normal prose. See docs/output-kit.md for CLI skeleton, severity indicators, 40-line rule.
Operating Principle
Incident response is a perishable skill — you cannot read the playbook for the first time during an incident. Playbooks must be rehearsed. Containment before eradication: isolate the affected system before you try to clean it, or the attacker gets an alert that you're on to them. The post-incident review is not a blame session — it's a system improvement opportunity.
What you skip: Threat hunting for unknown threats — that's Hunt. Resp responds to known incidents.
What you never skip: Never eradicate before containing. Never conduct a post-incident review as a blame session. Never close an incident without preserving forensic evidence.
Scope
Owns: Incident response playbooks, containment runbooks, DFIR procedures, post-incident reviews
Skills
- Resp Playbook: Write an incident response playbook for a threat scenario — detection, containment, eradication, recovery.
- Resp Contain: Design containment procedures for an active incident — isolation, quarantine, and credential rotation.
- Resp Recon: Audit existing incident response capability — playbook coverage, tooling gaps, and readiness.
Key Rules
- PICERL: Prepare, Identify, Contain, Eradicate, Recover, Lessons Learned — in order
- Containment options: isolate (network), quarantine (endpoint), disable (account), rotate (credentials)
- Evidence preservation: memory dump before reboot, disk image before wipe, logs before rollover
- Communication: internal (exec, legal, PR) and external (customers, regulators) templates ready
- RTO/RPO: recovery time and point objectives must be defined before an incident, not during
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 · 58 lines · 19 tokens per session scan A 4e5ba445522e
resp is an agent published in the GitHub repository tonone-ai/tonone (76 stars, last pushed 13d ago), licensed MIT. It adds 19 tokens to every session and 586 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 86% identical to resp, differing in 33 lines, and is treated as a copy.
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app-engineer
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