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stepsecurity-mcp

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get_threat_incident

Retrieve full details of a security threat incident, including compromised package names, versions, and C2 domains/IPs. After listing incidents, use this to extract concrete IOCs and determine which exposure checks to run based on the ecosystem (npm or pypi).

Instructions

Get full details of one threat-center incident — including the 'Am I Affected?' markdown section which lists the EXACT compromised package names + versions and C2 IOCs (domains/IPs) to check. Call this after list_threat_incidents to extract the concrete things to search for. The incident's ecosystem field ('npm' or 'pypi') dictates which exposure tools to call: for npm → check_npm_package_exposure + check_npm_package_on_dev_machines. For pypi → check_pypi_package_exposure + check_python_package_on_dev_machines. Always also call check_ioc_in_baseline for each C2 domain/IP mentioned, regardless of ecosystem.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ownerYesGitHub organization
incidentIdYesIncident UUID from list_threat_incidents
Behavior4/5

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

No annotations provided; description carries full burden. It describes what the return includes (compromised packages, IOCs), but doesn't explicitly state read-only nature or auth requirements, though implied.

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

Conciseness4/5

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

Two sentences, no filler; second sentence is a bit long but packs useful instructions. Efficient overall.

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?

No output schema, but description explains return content (markdown with exact data). Complete enough for agent to know what to expect.

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?

Schema coverage is 100% with clear descriptions; description adds context (e.g., incidentId from list_threat_incidents) but not significantly more than schema.

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?

Description clearly states 'Get full details of one threat-center incident' with specific content (markdown section), distinguishing it from sibling list_threat_incidents.

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

Usage Guidelines5/5

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

Explicitly says to call after list_threat_incidents, and gives detailed follow-up actions based on ecosystem (npm vs pypi) and always check_ioc_in_baseline.

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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