Mandate 2.4.1 Runtime Evidence Intake and Guidance Skill
Mandate
- ID: 2.4.1
- Title: Resource Consumption Limits
Mitigates
- LLM10 Unbounded Consumption
- ASI02 Tool Misuse and Exploitation
- MCP04 Tool Interference
Purpose
Collect user-provided context in natural language, convert it into an evidence plan, and produce actionable steps and commands to generate runtime/process evidence for final assessment.
Step-by-Step Workflow
- Elicit context in natural language. Ask for environment stack, deployment model, cloud/on-prem platform, logging/identity/security tooling, and data sensitivity profile.
- Normalize context. Convert user responses into a structured environment profile: systems, owners, data stores, auth layers, monitoring tools.
- Build mandate evidence matrix. Map required evidence types to concrete systems and responsible owners.
- Generate evidence collection plan. Provide ordered steps to extract artifacts, expected output formats, and validation checks.
- Generate system command pack. Produce commands with placeholders for the user environment and explain expected outputs.
- Validate completeness. Mark each required artifact as collected, partial, or missing.
- Produce final readiness report. Summarize what is sufficient for final pass/fail and what gaps remain.
Runtime/Process Evidence Required
- Runtime quota/rate-limit configuration from gateway/orchestrator.
- Enforcement logs showing blocked/throttled events.
- Capacity monitoring dashboards and alert thresholds.
- Cost anomaly and abuse incident records.
Minimum User Inputs to Start
- Production limit configs (API gateway, job scheduler, container runtime).
- Recent throttle/rejection event logs.
- Monitoring and alerting snapshots.
Command Templates (Adapt to User Environment)
- Kubernetes limits/quotas: kubectl get limitrange -A && kubectl get resourcequota -A
- API gateway throttling settings: cat api_rate_limit_config_.yaml
- Runtime rejection/throttle logs: cat throttle_events_.jsonl
- Resource monitoring snapshots: cat resource_utilization_.csv
- Cost anomaly events: cat cost_anomalies_.json
Final Evaluation Logic
- Pass only if code-defined controls exist and runtime evidence shows consistent enforcement across all entry points.
- Fail if any major path lacks proven runtime quota enforcement.
Output Contract
Return:
- context_profile: normalized system context
- evidence_requirements: checklist by artifact
- command_plan: runnable command templates with placeholders
- collection_status: per-artifact status
- assessment_readiness: ready|not_ready
- remaining_gaps: missing evidence blocking final verdict
Guardrails
- Ask concise follow-up questions when context is ambiguous.
- Keep commands read-only by default.
- Call out commands requiring elevated privileges before execution.