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snooze_issue

Snooze an issue and all its current and future occurrences by selecting a reason: risk acceptance, false positive, or mitigating controls.

Instructions

    Snooze an issue and all its current and future occurrences.

    Args:
        issue_id: The ID of the issue to snooze
        reason: Reason for snoozing (required, must 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
reasonYes
detailsNo
durationNo
duration_typeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • MCP tool handler that snoozes an issue via the Intruder API. Decorated with @mcp.tool() and registered as the 'snooze_issue' tool.
    @mcp.tool()
    async def snooze_issue(issue_id: int, reason: str, details: Optional[str] = None, duration: Optional[int] = None, duration_type: Optional[str] = None) -> str:
        """
        Snooze an issue and all its current and future occurrences.
    
        Args:
            issue_id: The ID of the issue to snooze
            reason: Reason for snoozing (required, must 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_issue(issue_id, reason=reason, details=details, duration=duration, duration_type=duration_type)
        return result.get("message", str(result))
  • Registration of the snooze_issue tool via the @mcp.tool() decorator on line 268. The FastMCP instance is 'mcp', created on line 20.
    @mcp.tool()
    async def snooze_issue(issue_id: int, reason: str, details: Optional[str] = None, duration: Optional[int] = None, duration_type: Optional[str] = None) -> str:
        """
        Snooze an issue and all its current and future occurrences.
    
        Args:
            issue_id: The ID of the issue to snooze
            reason: Reason for snoozing (required, must 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_issue(issue_id, reason=reason, details=details, duration=duration, duration_type=duration_type)
        return result.get("message", str(result))
  • API client method that sends a POST request to /issues/{issue_id}/snooze/ using the SnoozeIssueRequest model and returns the JSON response.
    def snooze_issue(self, issue_id: int, reason: IssueSnoozeReasonEnum, details: Optional[str] = None, duration: Optional[int] = None, duration_type: Optional[str] = None) -> dict:
        data = SnoozeIssueRequest(details=details, duration=duration, duration_type=duration_type, reason=reason)
        return self.client.post(f"{self.base_url}/issues/{issue_id}/snooze/", json=data.dict(exclude_none=True)).json()
  • Pydantic model for the snooze issue request body with details, duration, duration_type, and reason (IssueSnoozeReasonEnum).
    class SnoozeIssueRequest(BaseModel):
        details: Optional[str] = None
        duration: Optional[int] = None
        duration_type: Optional[str] = None  # Should match DurationTypeEnum if defined
        reason: IssueSnoozeReasonEnum
  • Enum defining the valid reasons for snoozing an issue: ACCEPT_RISK, FALSE_POSITIVE, MITIGATING_CONTROLS.
    class IssueSnoozeReasonEnum(str, Enum):
        ACCEPT_RISK = "ACCEPT_RISK"
        FALSE_POSITIVE = "FALSE_POSITIVE"
        MITIGATING_CONTROLS = "MITIGATING_CONTROLS"
Behavior3/5

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

No annotations provided, so description carries the burden. It explains snoozing applies to current and future occurrences and defines reason meanings. However, it omits side effects like reversibility, notification impact, or unsnoozing behavior.

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?

Description is fairly concise, using a docstring structure. It front-loads the main action and provides parameter details. The reason explanations add value without excessive verbosity.

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?

Adequate for basic usage: defines parameters and reason meanings. But lacks details on unsnoozing, expiration behavior, and any side effects. Output schema exists but is not described. Overall, gaps in complete understanding remain.

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

Parameters4/5

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

Schema coverage is 0%, but description lists all parameters with meanings. It clarifies that 'reason' is required with three specific values (enums not in schema), and notes optional parameters. Missing interaction details between duration and duration_type.

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 action: 'Snooze an issue and all its current and future occurrences.' It distinguishes from sibling 'snooze_occurrence' by specifying scope (all occurrences), and uses specific verb+resource.

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 when to use (for global snoozing vs individual occurrence) but does not explicitly state alternatives or when not to use. The reason explanations give context but no explicit usage guidance.

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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