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list_blocked_domain_calls

Get blocked outbound network call detections from Harden-Runner egress policy enforcement. Filter by status, customer, or GitHub org. Each result provides a clickable dashboard URL for investigation.

Instructions

List detections where Harden-Runner actively BLOCKED an outbound network call (egress-policy enforcement). Different from anomalous calls: blocked = the call was prevented; anomalous = the call happened but wasn't in baseline. Every result has a dashboard_url — when you present detections to the user you MUST include a clickable link per detection, not just the first one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
customerNoStepSecurity customer/tenant identifier. Optional — if omitted, falls back to STEP_SECURITY_CUSTOMER env var. Returns detections aggregated across ALL GitHub orgs installed under this tenant.
statusNoDetection status filter. Defaults to 'new'.
limitNoMax detections to return (1-200). Defaults to 50.
orgScopeNoOptional: restrict to a single GitHub org under this tenant (uses the owner-scoped endpoint instead of tenant-wide).
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description carries the full burden. It reveals that the tool returns only blocked detections and mandates clickable link presentation. However, it does not disclose auth requirements, rate limits, error behavior, or the fact that results can be empty, leaving some behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no unnecessary words. The first sentence conveys purpose and differentiation; the second provides critical output guidance. Every sentence is essential and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a list tool with four well-described parameters and no output schema, the description adequately covers purpose, differentiation, and output presentation. It lacks details on error handling, sorting, and whether results are paginated, but these are reasonable omissions given the schema covers limit and status.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, so the baseline is 3. The description adds minimal semantic value beyond the schema: it mentions the env var fallback for customer and the owner-scoped endpoint for orgScope, but these are inferred from schema. No new semantic context is provided for status or limit.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lists blocked outbound network calls due to egress-policy enforcement, and explicitly distinguishes it from anomalous calls. This differentiates it from its sibling 'list_anomalous_network_calls', providing high specificity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use this tool versus list_anomalous_network_calls by contrasting blocked vs anomalous. It also notes the requirement to present dashboard_url as clickable links, but does not provide explicit guidance on when not to use this tool or other alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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