Borrowing it
Nothing to install: this file belongs to Contoso-State/red-team-agent-orchestration. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Contoso-State/red-team-agent-orchestration/main/.claude/commands/assess.mdgit 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/commands/contoso-state/red-team-agent-orchestration/assess)<a href="https://agentmods.dev/commands/contoso-state/red-team-agent-orchestration/assess"><img src="https://agentmods.dev/badge/commands/contoso-state/red-team-agent-orchestration/assess/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/commands/contoso-state/red-team-agent-orchestration/assess"><img src="https://agentmods.dev/badge/commands/contoso-state/red-team-agent-orchestration/assess.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 | $0.00017 | $0.00921 |
| Opus 5 | $0.00009 | $0.00461 |
| Sonnet 5 | $0.00003 | $0.00184 |
| Haiku 4.5 | $0.00002 | $0.00092 |
Grade A, and why
assess 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 10d 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 — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/assess — Full Security Assessment
You are acting as the Orchestrator Agent (agents/orchestrator/system-prompt.md). Run the full domain assessment phase.
Preconditions
engagement.yamlexists and is valid.scope.subscriptionscontains exactly one target subscription.engagements/<session>/inventory/resources.jsonlexists (run/reconfirst if not).engagements/<session>/engagement.dbexists with the inventory ingested (run/reconfirst if not).
Steps
-
Confirm inventory is present and current. If missing, run reconnaissance first. Domain agents should read inventory and cached config facts from the datastore (
node tools/datastore/query.mjs resources|facts|neighbors --db engagements/<session>/engagement.db …) before calling Azure — only hitaz/ARG on a cache miss or a stale fact (query.mjs fresh … --ttl <seconds>). -
Dispatch domain agents based on resource types in the inventory. Each agent runs its checks from
checks/<domain>/and writes findings toengagements/<session>/findings/raw/<agent>.jsonl:Condition Agent Prompt Entra ID / app registrations in scope Identity Posture agents/identity-posture/system-prompt.mdNetwork resources / public IPs Network Exposure agents/network-exposure/system-prompt.mdCompute / AKS / Kubernetes / containers / functions Compute Platform agents/compute-platform/system-prompt.mdStorage / Key Vault / databases Data Protection agents/data-protection/system-prompt.mdCDN / Front Door / static sites / APIM / WAF Web & Static Sites agents/web-exposure/system-prompt.mdCognitive Services / Azure OpenAI / AI Foundry / ML AI & Foundry agents/ai-foundry/system-prompt.mdPublic IPs / DNS zones / internet-facing endpoints (always) Attack Surface (EASM) agents/attack-surface/system-prompt.mdAlways Logging Coverage agents/logging-coverage/system-prompt.mdAlways (control-plane guardrails) Governance & Posture agents/governance-posture/system-prompt.mdFederated credentials (OIDC) / ACR / Automation / Logic Apps / CI/CD SPs DevOps & Supply Chain agents/devops-supplychain/system-prompt.mdM365 / Exchange Online in scope (optional) Email Security agents/email-security/system-prompt.mdRole assignments / custom roles (after the above) Authorization & Attack Path agents/authorization-attack-path/system-prompt.md
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.
- 10d ago First seen · 50 lines · 17 tokens per session scan A 795f4047c959
assess is a command published in the GitHub repository Contoso-State/red-team-agent-orchestration (6 stars, last pushed 6d ago), licensed MIT. It adds 17 tokens to every session and 921 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 2026-08-31.
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