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/Contoso-State/red-team-agent-orchestrationWrote 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/rules/contoso-state/red-team-agent-orchestration/redteam-reporting)<a href="https://agentmods.dev/rules/contoso-state/red-team-agent-orchestration/redteam-reporting"><img src="https://agentmods.dev/badge/rules/contoso-state/red-team-agent-orchestration/redteam-reporting.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 5.1 | $0.00057 | $0.00399 |
| Opus 5 | $0.00028 | $0.00199 |
| Sonnet 5 | $0.00011 | $0.00080 |
| Haiku 4.5 | $0.00006 | $0.00040 |
Grade A, and why
redteam-reporting 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 4d 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.
What it actually says
Red Team — Reporting
Turn raw structured findings into deliverables a customer can act on. Reports are generated from findings data, never hand-authored.
Methodology: agents/reporting/system-prompt.md. Templates: reports/templates/.
Skill (domain knowledge): .github/skills/azure-redteam-reporting/SKILL.md.
Severity model: knowledge/severity-model.md.
Steps
- Ingest every
engagements/<session>/findings/raw/*.jsonl; validate againstschemas/finding.schema.json. - Deduplicate findings with the same root cause on the same resource; merge evidence.
- Prioritize via
knowledge/severity-model.md; attack-path chains rank by end state. - Render
engagements/<session>/reports/:executive-summary.md,technical-report.md, per-finding files. - Map findings to CIS (
controls/cis-azure.yaml) and MITRE (controls/mitre-cloud.yaml). - Write
engagements/<session>/findings/normalized/findings.jsonas the deduplicated source of truth.
Safety
Read-only. Honor data_handling in engagement.yaml — redact tenant/subscription IDs, UPNs, and
resource names if sanitization is required. Never include secret values or raw data samples.
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.
- 4d ago First seen · 29 lines · 57 tokens per session scan A 91d6e6b701f5
redteam-reporting is a cursor rule published in the GitHub repository Contoso-State/red-team-agent-orchestration (6 stars, last pushed 3d ago), licensed MIT. It adds 57 tokens to every session and 399 once invoked, about $0.0003 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 2026-09-03.
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