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Legion33shadow

legion-ai-intelligence

get_ai_incidents

Search classified AI agent security incidents by type and severity. Retrieve records like prompt injection or sandbox escapes to analyze threats and inform agent safety.

Instructions

Search classified AI agent security incidents. Types: api_exploit, sandbox_escape, prompt_injection, unauthorized_action, agent_escape, data_exfiltration. Severities: critical, high, medium, low.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNo
limitNo
severityNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden, yet it discloses no auth requirements, rate limits, pagination behavior, or how the default limit of 5 is applied. It conveys what is searched but nothing about how the operation behaves.

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, front-loaded with the core action followed by the valid enum values, with zero filler. Every clause earns its place.

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

Completeness2/5

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

Although an output schema exists (so return values need no explanation), the absence of annotations and 0% schema coverage means the description should carry behavioral and parameter detail it omits. It never explains the limit parameter or the default result set, leaving real gaps for invocation.

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 description coverage is 0%, so the description is the only source: it lists the valid values for the type and severity parameters, which substitutes for missing schema enums. However, the limit parameter (default 5) is never mentioned, leaving one of three parameters undocumented.

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?

States a specific verb (Search) and resource (classified AI agent security incidents), and the enumerated incident types and severities make the domain unambiguous. An agent can readily distinguish this from siblings like get_incident_stats or get_ai_regulations.

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

Usage Guidelines2/5

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

The description never says when to use this tool versus the alternatives. It does not mention get_incident_stats (statistics) as a sibling for aggregate views, nor does it state prerequisites or the conditions that select this tool.

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