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snooze_issue

Temporarily pause an issue and its occurrences in Intruder.IO by specifying a reason like ACCEPT_RISK, FALSE_POSITIVE, or MITIGATING_CONTROLS, with optional duration and details.

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

Implementation Reference

  • MCP tool handler and registration for 'snooze_issue'. Decorated with @mcp.tool() and implements the core logic by calling the API client's snooze_issue method.
    @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))
  • Pydantic schema model SnoozeIssueRequest used for input validation in the API client for snoozing issues.
    class SnoozeIssueRequest(BaseModel):
        details: Optional[str] = None
        duration: Optional[int] = None
        duration_type: Optional[str] = None  # Should match DurationTypeEnum if defined
        reason: IssueSnoozeReasonEnum
  • Helper method in IntruderAPI class that performs the actual HTTP POST request to snooze an issue using the SnoozeIssueRequest schema.
    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()
  • Enum defining valid reasons for snoozing an issue, used in SnoozeIssueRequest.
    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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly indicates this is a mutation operation ('snooze') that affects current and future occurrences, but doesn't specify permission requirements, whether snoozes are reversible, rate limits, or what happens to already-snoozed occurrences. It adds some context about the scope of effect but misses key behavioral details for a mutation tool.

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 a clear purpose statement followed by parameter documentation. Every sentence earns its place, though the bulleted list of reason meanings could be slightly more concise. The information is front-loaded with the core functionality stated first.

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?

For a mutation tool with 5 parameters, no annotations, and no output schema, the description does a good job with parameter semantics but lacks sufficient behavioral context. It doesn't explain what the tool returns, error conditions, or important side effects. While parameter coverage is excellent, the overall completeness is limited by missing mutation-specific behavioral details.

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, the description fully compensates by providing detailed parameter explanations. It documents all 5 parameters, specifies required vs optional status, explains the meaning of the 'reason' parameter with its three allowed values and their interpretations, and clarifies what 'duration' and 'duration_type' represent. This adds substantial value beyond the bare 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?

The description clearly states the specific action ('snooze') and resource ('an issue and all its current and future occurrences'), distinguishing it from the sibling tool 'snooze_occurrence' which likely handles individual occurrences rather than the entire issue chain. The verb+resource combination is precise and unambiguous.

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 implies usage context through the parameter explanations (e.g., reasons like 'ACCEPT_RISK'), but doesn't explicitly state when to use this tool versus alternatives like 'snooze_occurrence' or other issue management tools. It provides clear context about what the tool does but lacks explicit when/when-not 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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