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 jsgerman-oss/blackrim-nimbus-skills --skill alibaba-identity-and-securitygit clone --depth 1 https://github.com/jsgerman-oss/blackrim-nimbus-skillsWrote 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/jsgerman-oss/blackrim-nimbus-skills/alibaba-identity-and-security)<a href="https://agentmods.dev/skills/jsgerman-oss/blackrim-nimbus-skills/alibaba-identity-and-security"><img src="https://agentmods.dev/badge/skills/jsgerman-oss/blackrim-nimbus-skills/alibaba-identity-and-security/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/jsgerman-oss/blackrim-nimbus-skills/alibaba-identity-and-security"><img src="https://agentmods.dev/badge/skills/jsgerman-oss/blackrim-nimbus-skills/alibaba-identity-and-security.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 | $0.00090 | $0.02997 |
| Opus 5 | $0.00045 | $0.01499 |
| Sonnet 5 | $0.00018 | $0.00599 |
| Haiku 4.5 | $0.00009 | $0.00300 |
Grade A, and why
alibaba-identity-and-security 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 12d 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 — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Alibaba Identity and Security
When to use
- Writing or reviewing a RAM policy, role trust relationship, or STS assumption chain.
- Standing up a new account, sub-account structure, or Resource Management hierarchy.
- Rotating, scoping, or auditing AccessKey pairs and secrets.
- Setting up org-level guardrails (Cloud Config rules, Resource Management policies).
- Configuring ActionTrail, Cloud Firewall, Security Center, or Anti-DDoS posture.
- Investigating an incident — ActionTrail forensics, Cloud Firewall traffic analysis.
Identity model
- Humans → RAM users with MFA, or SAML federation from enterprise IdP (Okta, Entra ID, etc.). No long-lived AK/SK pairs for human users in production accounts. RAM sub-users are acceptable in small teams; for larger organizations, federate via SAML 2.0 SSO into the Alibaba Cloud console.
- Workloads → RAM Roles assumed by the runtime. ECS instance RAM Role, RRSA (RAM Role for Service Accounts) in ACK, FC service RAM Role. No static AK/SK in application code, environment variables, or container images.
- External CI/CD → OIDC federation with RAM Role trust. GitHub Actions OIDC → RAM Role; scoped by
subclaim to repo / ref. Never store an AK/SK in CI secrets. - Programmatic break-glass → STS AssumeRole with MFA, time-bounded, ActionTrail-logged. Keep break-glass credentials offline; rotate quarterly.
- China vs International: RAM policies, KMS keys, and account structures are entirely separate between China and International accounts. An AK/SK valid in one cannot authenticate to the other.
RAM policy discipline
- Default-deny. Every
Allowstatement is justified with a specific reason. - Resource-level ARNs, not
Resource: "*". If the service supports resource-level permissions, scope to the specific ARN pattern (e.g.,acs:oss:*:*:my-bucket/*). - Conditions for context:
acs:SourceIp,acs:SecureTransport,acs:MFAPresent,acs:RequestedRegion,acs:ResourceTag/Environment=prod. - Permission boundaries (RAM policies attached to roles that cap what the role can grant) for developer-provisioned roles.
- Resource Group policies at the account or resource-group level for org-wide guardrails.
- No inline policies for production roles — managed (custom or system) policies only, version-controlled.
- Policy linting: use the RAM policy visual editor or
aliyun ram SimulatePrincipalPolicyto verify before applying.
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.
- 12d ago First seen · 157 lines · 90 tokens per session scan A 296a26a12636
alibaba-identity-and-security is a skill published in the GitHub repository jsgerman-oss/blackrim-nimbus-skills (8 stars, last pushed 26d ago), licensed MIT. It adds 90 tokens to every session and 2,997 once invoked, about $0.0005 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.
Other skills, from other repositories
gke-compute-classes
Configures, optimizes, and troubleshoots GKE ComputeClasses. Use when configuring Spot VMs with on-demand fallback, targeting specific accelerators (GPUs/TPUs) or machine families, restricting ComputeClass access, or debugging pending pods related to node pool auto-creation. Do not use for cluster-level Node Auto…
gke-reliability
Improves GKE workload reliability, using PDBs, health probes, and topology spread constraints. Use when configuring GKE workload reliability, setting up PDBs, or configuring GKE health probes (liveness, readiness, startup). Don't use for disaster recovery setup or full cluster backups (use gke-backup-dr instead).
gke-workload-security
Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running cluster security audits (auditcluster.sh), configuring Workload Identity Federation (impersonation, KSA/GSA binding, and pod setup), enforcing Network Policies (default-deny…
nemo-automodel-launcher-config
Configure NeMo AutoModel job launches for interactive runs, Slurm clusters, and SkyPilot cloud execution.
azure-mgmt-botservice-dotnet
Azure Resource Manager SDK for Bot Service in .NET. Management plane operations for creating and managing Azure Bot resources, channels (Teams, DirectLine, Slack), and connection settings. Triggers: "Bot Service", "BotResource", "Azure Bot", "DirectLine channel", "Teams channel", "bot management .NET", "create bot".
cloud-architect
Designs cloud architectures, creates migration plans, generates cost optimization recommendations, and produces disaster recovery strategies across AWS, Azure, and GCP. Use when designing cloud architectures, planning migrations, or optimizing multi-cloud deployments. Invoke for Well-Architected Framework, cost…