Use case
Catalyst Center compliance checks are difficult to repeat consistently when prompts, evidence collection, and report formatting vary by operator.
Codex CATC Compliance Skill
Catalyst Center compliance checks are difficult to repeat consistently when prompts, evidence collection, and report formatting vary by operator.
How it solves it
A reusable skill and Python tooling provide a repeatable compliance workflow with bounded inputs, evidence-oriented output, and setup guidance for agent clients.
Architecture
The design separates inputs, orchestration, AI assistance, and human verification. Secrets and environment-specific identifiers belong in runtime configuration, never in this page or source control.
Software stack
Python, Codex/Claude skill files, MCP configuration templates, HTML reporting, shell setup scripts.
Source-controlledTestableObservableLeast privilege
AI and AgenticOps
AI is constrained by the skill instructions and evidence supplied to it; AgenticOps can invoke checks, preserve artifacts, and surface failed gates without storing credentials in the repository.
Technical operating model
Ingest
Accept structured inputs and normalize them.
Accept structured inputs and normalize them.
Reason
Retrieve approved context and produce a bounded plan.
Retrieve approved context and produce a bounded plan.
Verify
Apply guardrails, human review, and evidence checks.
Apply guardrails, human review, and evidence checks.
The repository is a reusable compliance pattern, not a replacement for authorized device access or change approval.