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/recon.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/recon)<a href="https://agentmods.dev/commands/contoso-state/red-team-agent-orchestration/recon"><img src="https://agentmods.dev/badge/commands/contoso-state/red-team-agent-orchestration/recon/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/recon"><img src="https://agentmods.dev/badge/commands/contoso-state/red-team-agent-orchestration/recon.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 | $0.00021 | $0.01359 |
| Opus 5.5 | $0.00008 | $0.00544 |
| Sonnet 5.5 | $0.00004 | $0.00272 |
| Haiku 4.5 | $0.00002 | $0.00136 |
Grade A, and why
recon 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.
How it starts
The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/recon — Reconnaissance & Inventory
You are acting as the Orchestrator Agent (agents/orchestrator/system-prompt.md). Begin a new red team engagement reconnaissance phase.
Steps
- Verify the environment. Run
node tools/preflight/check-environment.mjs. If any required check fails (Node ≥ 22.5, Azure CLI installed + signed in,resource-graphextension), show the doctor's remediation and stop until it passes — the inventory pipeline needs all of them. This is read-only. - Load scope. Read
engagement.yaml. If it does not exist, tell the user to copyengagement.example.yamltoengagement.yamland fill it in, then stop. - Validate scope against
schemas/engagement.schema.json. Echo a one-line summary: engagement ID, mode, target subscription, assessment focus (scope.domains/scope.resource_types), and any exclusions. Confirm with the user before proceeding if anything looks off.- Hard stop:
scope.subscriptionsmust contain exactly one subscription. If not, stop and require/setupto regenerateengagement.yamlfor a single-subscription run. - If no focus is set (
scope.resource_typesandscope.domainsboth empty), ask "What is your assessment focus for this subscription?" before enumerating — offer the focus menu (Full estate · Public/internet exposure · Virtual Machines & compute · Data stores · Identity & access · AI/Foundry · Logging & governance · DevOps & supply chain · or specific resource types like just VMs or just Public IPs). Pass the chosenscope.resource_typesto the Inventory agent so Resource Graph filters server-side.
- Hard stop:
3.5. Confirm identity, target, and mode — do not proceed until the user says yes.
Run az account show and present a full pre-flight confirmation block:
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 · 73 lines · 21 tokens per session scan A ba4656a382ed
recon is a command published in the GitHub repository Contoso-State/red-team-agent-orchestration (6 stars, last pushed 1mo ago), licensed MIT. It adds 21 tokens to every session and 1,359 once invoked, about $0.0001 per session on Opus 5.5. 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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