guard

MANDATORY PREPARATION

Invoke /agent-workflow — it contains workflow principles, anti-patterns, and the Context Gathering Protocol. Follow the protocol before proceeding — if no workflow context exists yet, you MUST run /teach-maestro first.

Consult the guardrails-safety reference in the agent-workflow skill for the full defense-in-depth framework.

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Add safety boundaries to a workflow. Guards protect against malicious inputs, unintended outputs, data leakage, cost explosion, and all the ways an autonomous system can go wrong in the real world.

Threat Assessment

Before adding guards, understand what you're protecting against:

Threat	Risk Level	Guard Type
Prompt injection	High	Input sanitization, instruction hierarchy
PII leakage	High	Output filtering, data masking
Cost explosion	High	Token budgets, rate limits
Unauthorized actions	Medium	Permission scoping, confirmation gates
Hallucination	Medium	Source attribution, fact checking
Service abuse	Medium	Rate limiting, authentication

Guard Implementation

Input Guards

Before processing any input:
1. Validate against schema (reject malformed)
2. Check size limits (reject oversized)
3. Sanitize for injection patterns
4. Rate limit check (reject if exceeded)
5. Authentication/authorization check

Output Guards

Before returning any output:
1. Schema validation (format correct?)
2. PII scan (names, emails, SSNs, etc.)
3. Content policy check
4. Confidence threshold check
5. Source attribution present?

Cost Guards

Before every model/API call:
1. Check remaining budget
2. Estimate request cost
3. If estimate > remaining budget → reject or use cheaper alternative
4. After call → update spent amount
5. Circuit breaker check (too many failures?)

Permission Guards

For every tool call:
1. Is this tool allowed for this user/context?
2. Is this a destructive operation? → require confirmation
3. Is this accessing data the user is authorized for?
4. Log the access for audit trail