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 aiappsgbb/awesome-gbb --skill foundry-rbac-auditgit clone --depth 1 https://github.com/aiappsgbb/awesome-gbbWrote 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/aiappsgbb/awesome-gbb/foundry-rbac-audit)<a href="https://agentmods.dev/skills/aiappsgbb/awesome-gbb/foundry-rbac-audit"><img src="https://agentmods.dev/badge/skills/aiappsgbb/awesome-gbb/foundry-rbac-audit/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/aiappsgbb/awesome-gbb/foundry-rbac-audit"><img src="https://agentmods.dev/badge/skills/aiappsgbb/awesome-gbb/foundry-rbac-audit.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 | $0.00198 | $0.01767 |
| Opus 5 | $0.00099 | $0.00883 |
| Sonnet 5 | $0.00040 | $0.00353 |
| Haiku 4.5 | $0.00020 | $0.00177 |
Grade A, and why
foundry-rbac-audit 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 — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
foundry-rbac-audit
Peer skill that probes Azure RBAC assignments at a resource-group scope for
privilege-escalation risks, returning a structured IAM-101 finding. It wraps
AuthorizationManagementClient via DefaultAzureCredential and never raises —
errors are captured in the returned dict. Threadlight v0.5.3+ consumes this as
the IAM-101 sibling-skill check in its threadlight-production-ready SEC-301
gate.
When to use
- Threadlight IAM-101 sibling-skill flip — threadlight's apply-plan reasoner
calls
probe()directly to satisfy the SEC-301 → IAM-101 check. - Pre-pilot security review of a Foundry-adjacent resource group before spoke onboarding — confirms no over-privileged principals hold Owner or equivalent roles.
- Scheduled CI check after team offboarding — detects residual privilege assignments; orphan-principal detection (deleted Entra IDs) is explicitly out of scope for v1.0.0.
When NOT to use
- Granting or revoking role assignments — use
az role assignment create/az role assignment deletedirectly. - Foundry-internal agent identity or per-agent-instance MI RBAC — use the
foundry-agtskill for identity lifecycle on hosted agents. - Hub-side Citadel checks — use
citadel-spoke-onboardingand itsprobe_hub_contractfor APIM/hub-scope governance.
Probe contract
The probe returns a dict matching the design spec §4.3.1 sibling-skill
contract. Signature and shape are stable across 1.x releases:
| Field | Type | Notes |
|---|---|---|
finding_id |
str | Always literal "IAM-101" |
scope |
dict (sub_id, rg) | Nested; not a string |
result |
enum ok / needs_attention / errored |
Never anything else |
observations |
list[dict] | Empty when result == "ok" |
remediation_hints |
list[str] | Empty when observations empty |
confidence |
0.0 / 0.5 / 1.0 | See Confidence heuristic below |
probed_at |
ISO-8601 UTC with Z |
tz-aware |
error |
str | None | None on success; "<Type>: <msg>" on errored |
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 150 lines · 198 tokens per session scan A 52d697995b83
foundry-rbac-audit is a skill published in the GitHub repository aiappsgbb/awesome-gbb (5 stars, last pushed 3d ago), licensed MIT. It adds 198 tokens to every session and 1,767 once invoked, about $0.0010 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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