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Overview

Interventions are records of when Agent Sentinel’s policy engine actively prevented or modified agent actions. The Interventions API provides:
  • Query endpoints for intervention history
  • Statistics showing “blast radius” avoided
  • Cost prevention metrics
  • Risk analysis

Endpoints

List interventions

Query parameters:
  • type (optional): Filter by intervention type
    • hard_block, approval_required, rate_limited, budget_exceeded, downgrade, warning
  • outcome (optional): Filter by outcome
    • blocked, escalated, approved_after_review, rejected_after_review, modified, warned
  • action_name (optional): Filter by action name (exact match)
  • agent_id (optional): Filter by agent ID
  • run_id (optional): Filter by run ID
  • policy_id (optional): Filter by policy that triggered intervention
  • risk_level (optional): Filter by risk level
    • critical, high, medium, low, minimal
  • start_date (optional): Filter by date range start (ISO 8601)
  • end_date (optional): Filter by date range end (ISO 8601)
  • skip (optional): Pagination offset (default: 0)
  • limit (optional): Page size (default: 50, max: 1000)
Example:
Response:

Get intervention details

Returns detailed information about a specific intervention.

Intervention statistics

Returns aggregate statistics showing platform value:

Create intervention (SDK)

Interventions are primarily created automatically by the SDK when policies trigger, but can also be created manually:

Delete intervention

Remove an intervention record (rare - usually for testing):

Intervention types

Guardrail context payloads

For Phase 7 guardrail blocks, the SDK populates intervention.context with a versioned, typed payload so the console can render a dedicated detail panel:
The guardrail discriminator is one of pii, moderation, loop, or idempotency. See Console → Interventions for how each panel renders.

Enriched fields

After ingest, a Gemini background task overwrites the following fields with plain-English versions (the original strings are preserved on the intervention’s audit trail):
  • reason — one or two sentences explaining the policy concern
  • agent_intent — what the agent was likely trying to accomplish
  • risk_level — reassessed severity
  • remediation_payload.suggested_rewrite — how the agent could safely retry, or null
Enrichment runs out-of-band, so the SDK’s POST /api/v1/ingest/ returns immediately and the enriched fields stream into the console asynchronously. Requires GEMINI_API_KEY (or GOOGLE_API_KEY) on the platform; degrades silently when absent. See SDK → LLM integrations.

Intervention outcomes

Risk levels

Use cases

Platform value demonstration

Show stakeholders what disasters were prevented:

Security monitoring

Monitor attempted policy violations:

Policy tuning

Identify policies that trigger frequently (may need adjustment):

Agent behavior analysis

Understand which agents are most frequently blocked:

Web console

View interventions in the web console:
  1. Navigate to Interventions page
  2. See dashboard with:
    • Total interventions
    • Cost saved
    • High-risk blocks
    • Blocked actions count
  3. Filter by type, outcome, risk level
  4. Click intervention for details including blast radius analysis
  5. Link to adjust triggering policy

Best practices

Review interventions regularly: High intervention rates may indicate overly restrictive policies or misbehaving agents.
Use blast radius field: Document what would have happened if the action was allowed - this demonstrates platform ROI.
Track cost prevented: Even if estimated_cost_usd is 0, interventions prevent non-monetary harm (data loss, reputation damage).
Don’t rely solely on interventions: Some actions may slip through if policies aren’t comprehensive. Use interventions as defense-in-depth.

See also

  • SDK Interventions - SDK-side intervention tracking
  • Policies - Configure policies that trigger interventions
  • Approvals - Human-in-the-loop workflow for escalated actions