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snooze_occurrence

Temporarily postpone a specific security issue occurrence in Intruder.IO by specifying a reason like false positive, accepted risk, or mitigating controls, with optional duration and details.

Instructions

    Snooze a specific occurrence of an issue.

    Args:
        issue_id: The ID of the issue
        occurrence_id: The ID of the occurrence to snooze
        reason: Reason for snoozing (required, must be one of ACCEPT_RISK, FALSE_POSITIVE, MITIGATING_CONTROLS)
        details: Optional details for the snooze
        duration: Optional duration for the snooze (in seconds)
        duration_type: Optional duration type (e.g., 'days', 'hours')
        
    The reasons mean:
        - ACCEPT_RISK - Risk accepted for the issue and all of its occurrences
        - FALSE_POSITIVE - False positive - issue and all occurrences have been verified as not exploitable
        - MITIGATING_CONTROLS - Mitigating controls are in place
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
issue_idYes
occurrence_idYes
reasonYes
detailsNo
durationNo
duration_typeNo

Implementation Reference

  • The MCP tool handler for 'snooze_occurrence', decorated with @mcp.tool() for automatic registration. It calls the IntruderAPI to snooze a specific occurrence and returns the result message.
    @mcp.tool()
    async def snooze_occurrence(issue_id: int, occurrence_id: int, reason: str, details: Optional[str] = None, duration: Optional[int] = None, duration_type: Optional[str] = None) -> str:
        """
        Snooze a specific occurrence of an issue.
    
        Args:
            issue_id: The ID of the issue
            occurrence_id: The ID of the occurrence to snooze
            reason: Reason for snoozing (required, must be one of ACCEPT_RISK, FALSE_POSITIVE, MITIGATING_CONTROLS)
            details: Optional details for the snooze
            duration: Optional duration for the snooze (in seconds)
            duration_type: Optional duration type (e.g., 'days', 'hours')
            
        The reasons mean:
            - ACCEPT_RISK - Risk accepted for the issue and all of its occurrences
            - FALSE_POSITIVE - False positive - issue and all occurrences have been verified as not exploitable
            - MITIGATING_CONTROLS - Mitigating controls are in place
        """
        result = api.snooze_occurrence(issue_id, occurrence_id, reason=reason, details=details, duration=duration, duration_type=duration_type)
        return result.get("message", str(result))
  • Pydantic schema models (OccurrencesSnoozeReasonEnum and SnoozeOccurrenceRequest) defining the input validation for snoozing occurrences, used by the API client.
    class OccurrencesSnoozeReasonEnum(str, Enum):
        ACCEPT_RISK = "ACCEPT_RISK"
        FALSE_POSITIVE = "FALSE_POSITIVE"
        MITIGATING_CONTROLS = "MITIGATING_CONTROLS"
    
    class SnoozeIssueRequest(BaseModel):
        details: Optional[str] = None
        duration: Optional[int] = None
        duration_type: Optional[str] = None  # Should match DurationTypeEnum if defined
        reason: IssueSnoozeReasonEnum
    
    class SnoozeOccurrenceRequest(BaseModel):
        details: Optional[str] = None
        duration: Optional[int] = None
        duration_type: Optional[str] = None  # Should match DurationTypeEnum if defined
        reason: OccurrencesSnoozeReasonEnum 
  • IntruderAPI helper method that constructs the request using the schema and performs the HTTP POST to the Intruder API endpoint for snoozing an occurrence.
    def snooze_occurrence(self, issue_id: int, occurrence_id: int, reason: OccurrencesSnoozeReasonEnum, details: Optional[str] = None, duration: Optional[int] = None, duration_type: Optional[str] = None) -> dict:
        data = SnoozeOccurrenceRequest(details=details, duration=duration, duration_type=duration_type, reason=reason)
        return self.client.post(f"{self.base_url}/issues/{issue_id}/occurrences/{occurrence_id}/snooze/", json=data.dict(exclude_none=True)).json() 
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes what the tool does (snoozes an occurrence) and explains parameter meanings, but doesn't disclose critical behavioral traits like whether this is a destructive/mutative operation, what permissions are required, whether it's idempotent, what happens to other occurrences, or what the response looks like. For a mutation tool with zero annotation coverage, this leaves significant gaps.

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?

The description is appropriately sized and well-structured with clear sections: a purpose statement, parameter list with explanations, and detailed reason definitions. Every sentence adds value, though the formatting with bullet points for reasons is slightly verbose but justified given the complexity of the enum values.

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

Completeness3/5

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

Given this is a mutation tool with 6 parameters, no annotations, and no output schema, the description provides good parameter documentation but lacks critical behavioral context. It doesn't explain what 'snooze' actually means operationally, what the tool returns, error conditions, or side effects. The parameter coverage is excellent, but overall completeness is limited by missing behavioral transparency.

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

Parameters5/5

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

With 0% schema description coverage (titles only, no descriptions), the description provides comprehensive parameter semantics beyond what the schema offers. It explains each parameter's purpose, clarifies that 'reason' is required with specific enum values, provides detailed explanations of what each reason means, and indicates which parameters are optional. This fully compensates for the schema's lack of descriptions.

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 specific action ('Snooze a specific occurrence of an issue') with the exact resource ('occurrence of an issue'), distinguishing it from the sibling tool 'snooze_issue' which presumably snoozes the entire issue rather than a specific occurrence. The verb 'snooze' is precise and the scope is well-defined.

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

Usage Guidelines3/5

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

The description implies usage context through the parameter explanations (e.g., reason meanings), but doesn't explicitly state when to use this tool versus alternatives like 'snooze_issue' or other issue management tools. It provides some guidance through the parameter semantics but lacks explicit when/when-not instructions or named 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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