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/redteam-graph.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/redteam-graph)<a href="https://agentmods.dev/commands/contoso-state/red-team-agent-orchestration/redteam-graph"><img src="https://agentmods.dev/badge/commands/contoso-state/red-team-agent-orchestration/redteam-graph/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/redteam-graph"><img src="https://agentmods.dev/badge/commands/contoso-state/red-team-agent-orchestration/redteam-graph.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 | $0.00012 | $0.00546 |
| Opus 5.5 | $0.00005 | $0.00218 |
| Sonnet 5.5 | $0.00002 | $0.00109 |
| Haiku 4.5 | $0.00001 | $0.00055 |
Grade A, and why
redteam-graph 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 — 29 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Azure Red Team — Graph Orchestration Standard
Every engagement in this framework runs as ONE explicit, declarative graph. The single source of truth is graph/redteam.graph.json (redteam-azure v2.1.0): 15 nodes over a 12-specialist read-only roster, validated by tools/graph/validate-graph.mjs.
Two engines, one graph
- Dependency-free Node runner —
tools/graph/run-graph.mjs— executes simulated dispatch. The separatetools/graph/run-live.mjsuses a scoped Claude live adapter and fresh preflight; other runtimes use native agent orchestration. - First-class LangGraph target —
integrations/langgraph/— compiles the same JSON into a PythonStateGraphfor deployment.
Control flow
validate_scope (one subscription + read-only attestation) -> memory_load -> preflight_inventory -> build_security_context -> scoped Send fan-out (plan_specialists -> run_specialist) -> deterministic fan-in merge (collect_raw) -> bounded evaluator-optimizer reflection loop (evaluate, max_revisions=2, quality_threshold=0.85) -> Agent-as-a-Judge false-positive gate (judge) -> human-authorized active lanes (authorize_active interrupt) -> correlate -> report -> reflexion_debrief.
Self-improving loops (primary standard)
The evaluator-optimizer cycle, the Agent-as-a-Judge gate, and the reflexion debrief are enabled by default with evidence-gated methodology promotion and an explicit off override — tools/graph/self-improve.mjs. Cross-run learning is written ONLY to the memory/methodology/ namespace.
Immutable boundary
Read-only enforcement in guardrails/guard.mjs sits OUTSIDE the learning surface. Self-improvement can never modify guardrails/** or any guardrail namespace — that firewall is the one thing the graph cannot rewrite.
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 Changed d60cc6d4a75c
- 1mo ago Changed 24b94c949b1b
- 1mo ago First seen · 29 lines · 12 tokens per session scan A 49291160599b
redteam-graph is a command published in the GitHub repository Contoso-State/red-team-agent-orchestration (6 stars, last pushed 1mo ago), licensed MIT. It adds 12 tokens to every session and 546 once invoked, about $0.0000 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.