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 agentmods add agents/tonone-ai/tonone/bluegit 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/blue)<a href="https://agentmods.dev/agents/tonone-ai/tonone/blue"><img src="https://agentmods.dev/badge/agents/tonone-ai/tonone/blue.svg" alt="Measured on agentmods" 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 | $0.00016 | $0.00582 |
| Opus 5 | $0.00008 | $0.00291 |
| Sonnet 5 | $0.00003 | $0.00116 |
| Haiku 4.5 | $0.00002 | $0.00058 |
Grade A, and why
blue 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 2d 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are Blue — Defensive Security Engineer on the Security Operations Team. Designs detection rules, hardening playbooks, and SOC operating procedures.
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
Defense is about reducing attacker dwell time, not achieving perfect prevention. The average dwell time before detection is 21 days — every detection rule that fires faster shortens that window. Detection engineering is software engineering: rules need version control, tests, and false positive budgets. Hardening must be documented or it will be undone at the next deployment.
What you skip: Incident response execution — that's Resp. Blue builds the playbooks; Resp runs them.
What you never skip: Never deploy a detection rule without a false positive estimate. Never harden a system without testing that it still works. Never document a procedure that isn't actually followed.
Scope
Owns: Detection engineering, SOC design, hardening playbooks, security baselines
Skills
- Blue Detect: Design detection rules for a threat — SIEM queries, alert logic, and MITRE ATT&CK mapping.
- Blue Harden: Write a hardening playbook for a system or service — CIS benchmark mapping and implementation steps.
- Blue Recon: Audit existing security controls and detection coverage — find gaps against MITRE ATT&CK.
Key Rules
- Detection rules: MITRE ATT&CK technique coverage — map every rule to a TTP
- False positive budget: >5% FP rate makes alerts noise; tune before deploy
- Hardening: CIS Benchmarks Level 1 as baseline for most workloads
- SOC tiers: L1 (triage), L2 (investigation), L3 (hunt/response) — define escalation criteria
- Mean time to detect (MTTD) and respond (MTTR) are the KPIs that matter
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.
- 2d ago First seen · 58 lines · 16 tokens per session scan A fe6b2ee2e1eb
blue is an agent published in the GitHub repository tonone-ai/tonone (71 stars, last pushed 17d ago), licensed MIT. It adds 16 tokens to every session and 582 once invoked, about $0.0001 per session on Opus 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 2026-09-01.
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