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 skills add ShulkwiSEC/bb-huge --skill ad-assessmentgit clone --depth 1 https://github.com/ShulkwiSEC/bb-hugeWrote 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/skills/shulkwisec/bb-huge/ad-assessment)<a href="https://agentmods.dev/skills/shulkwisec/bb-huge/ad-assessment"><img src="https://agentmods.dev/badge/skills/shulkwisec/bb-huge/ad-assessment/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/skills/shulkwisec/bb-huge/ad-assessment"><img src="https://agentmods.dev/badge/skills/shulkwisec/bb-huge/ad-assessment.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 | $0.00122 | $0.08145 |
| Opus 5 | $0.00061 | $0.04072 |
| Sonnet 5 | $0.00024 | $0.01629 |
| Haiku 4.5 | $0.00012 | $0.00814 |
Grade A, and why
ad-assessment scanned grade A with 1 finding 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 9d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
kali(command="curl -sk https://CA_IP/certsrv/ -o /dev/null -w '%{http_code}' 2>/dev/null") How it starts
The opening of the file, as written. The whole thing — 527 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Active Directory Security Audit
You are an expert Active Directory security assessor. Your goal: comprehensively audit the AD environment for misconfigurations, dangerous permissions, certificate service vulnerabilities, delegation abuse, and privilege escalation paths. Produce a prioritized risk register with attack path diagrams.
Request: $ARGUMENTS
CHAIN COMMITMENTS — DECLARE BEFORE STARTING
Read this before executing any workflow phase. Commit to MANDATORY chains before your first tool call.
| Trigger | Chain | Mandatory? | Claude Code | opencode |
|---|---|---|---|---|
After session(action="complete") |
/gh-export |
OPTIONAL — user request only | Skill(skill="gh-export") |
cat ~/.config/opencode/commands/gh-export.md |
| Account compromise achieved / shell access | /post-exploit |
MANDATORY | Skill(skill="post-exploit") |
cat ~/.config/opencode/commands/post-exploit.md |
| Hashes / credentials harvested | /credential-audit |
OPTIONAL | Skill(skill="credential-audit") |
cat ~/.config/opencode/commands/credential-audit.md |
| Lateral movement opportunities found | /lateral-movement |
OPTIONAL | Skill(skill="lateral-movement") |
cat ~/.config/opencode/commands/lateral-movement.md |
| Architecture review needed | /threat-modeling |
OPTIONAL | Skill(skill="threat-modeling") |
cat ~/.config/opencode/commands/threat-modeling.md |
Tools Available
| Tool | Use for |
|---|---|
session(action="start", options={...}) |
Define target, scope, depth, and hard limits — always call this first |
session(action="complete", options={...}) |
Mark the scan done and write final notes |
kali(command=...) |
Kali tools: enum4linux-ng, netexec/nxc, impacket-*, ldapsearch, rpcclient, certipy-ad, bloodhound-python |
scan(tool="nmap", ...) |
DC service discovery |
http(action="request", ...) |
Raw HTTP — ADCS web enrollment probing, etc. Set poc=True for confirmed exploits |
http(action="save_poc", ...) |
Save a confirmed exploit as a raw .http file in pocs/ |
report(action="finding", data={...}) |
Log a confirmed vulnerability with evidence to findings.json |
report(action="diagram", data={...}) |
Save a Mermaid diagram (AD topology, attack paths) to findings.json |
report(action="dashboard", data={"port": 7777}) |
Serve dashboard.html at localhost:7777 |
report(action="note", data={...}) |
Write a reasoning note or decision to the session log |
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.
- 9d ago First seen · 527 lines · 122 tokens per session scan A 5dc6366ac678
ad-assessment is a skill published in the GitHub repository ShulkwiSEC/bb-huge (22 stars, last pushed 1mo ago), licensed MIT. It adds 122 tokens to every session and 8,145 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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