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list_occurrences

Fetches all occurrences for a given issue ID, with optional filters on target addresses, tag names, and snoozed status.

Instructions

    List all occurrences for a specific issue with optional filters.

    Args:
        issue_id: The ID of the issue to list occurrences for
        target_addresses: Filter by a list of target addresses
        tag_names: Filter by a list of tag names
        snoozed: Filter by snoozed status (true or false)
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
issue_idYes
target_addressesNo
tag_namesNo
snoozedNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The main tool handler for 'list_occurrences'. It's decorated with @mcp.tool() and accepts issue_id, target_addresses, tag_names, and snoozed parameters. It calls api.get_issue_occurrences_all() and formats the results as a string.
    async def list_occurrences(issue_id: int,
                             target_addresses: Optional[List[str]] = None,
                             tag_names: Optional[List[str]] = None,
                             snoozed: Optional[bool] = None) -> str:
        """
        List all occurrences for a specific issue with optional filters.
    
        Args:
            issue_id: The ID of the issue to list occurrences for
            target_addresses: Filter by a list of target addresses
            tag_names: Filter by a list of tag names
            snoozed: Filter by snoozed status (true or false)
        """
        occurrences = api.get_issue_occurrences_all(
            issue_id=issue_id,
            target_addresses=target_addresses,
            tag_names=tag_names,
            snoozed=snoozed
        )
        formatted = [f"{occ.id} - {occ.target}:{occ.port}/{occ.protocol}" for occ in occurrences]
        return "\n".join(formatted)
  • The tool is registered via the @mcp.tool() decorator on line 106, which is part of the FastMCP framework registration pattern.
    @mcp.tool()
    async def list_occurrences(issue_id: int,
  • Helper function 'get_issue_occurrences_all' that paginates through all occurrences for a given issue, calling get_issue_occurrences in a loop with offset-based pagination.
    def get_issue_occurrences_all(self, issue_id: int, snoozed: Optional[bool] = None,
                                 tag_names: Optional[List[str]] = None,
                                 target_addresses: Optional[List[str]] = None) -> Generator[Occurrence, None, None]:
        offset = 0
        while True:
            response = self.get_issue_occurrences(issue_id, snoozed=snoozed, tag_names=tag_names,
                                                target_addresses=target_addresses, limit=100, offset=offset)
            for occurrence in response.results:
                yield occurrence
            if not response.next:
                break
            offset += len(response.results)
  • Helper function 'get_issue_occurrences' that makes the actual API call to GET /issues/{issue_id}/occurrences/ with query parameters.
    def get_issue_occurrences(self, issue_id: int, snoozed: Optional[bool] = None,
                             tag_names: Optional[List[str]] = None,
                             target_addresses: Optional[List[str]] = None,
                             limit: Optional[int] = None, offset: Optional[int] = None) -> PaginatedOccurrenceList:
        params = {}
        if snoozed is not None:
            params["snoozed"] = snoozed
        if tag_names:
            params["tag_names"] = tag_names
        if target_addresses:
            params["target_addresses"] = target_addresses
        if limit:
            params["limit"] = limit
        if offset:
            params["offset"] = offset
        return PaginatedOccurrenceList(**self.client.get(f"{self.base_url}/issues/{issue_id}/occurrences/", params=params).json())
Behavior2/5

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

No annotations are provided, so the description carries full burden. It does not disclose whether the operation is read-only, safe, or has side effects. It lacks details on pagination, rate limits, or data completeness.

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 front-loaded with a clear purpose sentence, followed by a compact parameter listing. It is not overly verbose, but the parameter section largely duplicates information available in the schema's titles, so slightly redundant.

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 simple list operation with an output schema, the description is adequate. However, it lacks details on pagination, ordering, or whether 'all occurrences' implies unbounded results. This leaves minor gaps for an AI agent.

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?

With 0% schema description coverage, the description adds meaning by labeling parameters as filters (e.g., 'Filter by a list of target addresses'). However, it does not explain behavior when multiple filters are combined or provide format constraints beyond what the schema implies.

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 'List all occurrences for a specific issue with optional filters,' which uses a specific verb and resource. The phrase 'for a specific issue' distinguishes it from sibling tools like list_issues or list_scans, which list different entities.

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 provides no guidance on when to use this tool versus alternatives (e.g., snooze_occurrence) or any prerequisites. It simply states what it does without context on use cases.

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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