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list_issues_with_journals

Retrieve issues with full comment history to track progress by assignee, project, or status.

Instructions

Returns a list of issues with all comments. Useful for reviewing progress per assignee.

Args:
    assigned_to_id: Assignee ID (obtain via list_users)
    project_id: Project ID (all projects if omitted)
    status_id: Status ID or "open" / "closed" / "*"
    limit: Number of issues to fetch (max 100)
    offset: Starting offset

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assigned_to_idNo
project_idNo
status_idNo
limitNo
offsetNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The core implementation of the tool, which fetches issues and their associated journals from the Redmine API.
    def list_issues_with_journals(
        self,
        assigned_to_id: Optional[int] = None,
        project_id: Optional[str] = None,
        status_id: Optional[str] = None,
        limit: int = 25,
        offset: int = 0,
    ) -> List[Dict[str, Any]]:
        try:
            kwargs: Dict[str, Any] = {"limit": limit, "offset": offset}
            if assigned_to_id is not None:
                kwargs["assigned_to_id"] = assigned_to_id
            if project_id is not None:
                kwargs["project_id"] = project_id
            if status_id is not None:
                kwargs["status_id"] = status_id
            issues = self._redmine.issue.filter(**kwargs)
            result = []
            for issue in issues:
                full = self._redmine.issue.get(issue.id, include=["journals"])
                journals = _safe(full, "journals", [])
                result.append({
                    "id": full.id,
                    "subject": full.subject,
                    "status": _safe(_safe(full, "status"), "name", ""),
                    "tracker": _safe(_safe(full, "tracker"), "name", ""),
                    "priority": _safe(_safe(full, "priority"), "name", ""),
                    "assigned_to": _safe(_safe(full, "assigned_to"), "name", ""),
                    "updated_on": str(_safe(full, "updated_on", "")),
                    "journals": [
                        {
                            "notes": _safe(j, "notes", ""),
                            "created_on": str(_safe(j, "created_on", "")),
                            "user": _safe(_safe(j, "user"), "name", ""),
                        }
                        for j in journals
                        if _safe(j, "notes")
                    ],
                })
            return result
        except (AuthError, ForbiddenError) as e:
            raise RedmineError(f"Authentication failed: {e}") from e
        except Exception as e:
            raise RedmineError(f"list_issues_with_journals failed: {e}") from e
  • The interface layer that exposes the list_issues_with_journals tool, delegating the logic to the Redmine server client.
    def list_issues_with_journals(
        assigned_to_id: Optional[int] = None,
        project_id: Optional[str] = None,
        status_id: Optional[str] = None,
        limit: int = 25,
        offset: int = 0,
    ) -> List[Dict[str, Any]]:
        """Returns a list of issues with all comments. Useful for reviewing progress per assignee.
    
        Args:
            assigned_to_id: Assignee ID (obtain via list_users)
            project_id: Project ID (all projects if omitted)
            status_id: Status ID or "open" / "closed" / "*"
            limit: Number of issues to fetch (max 100)
            offset: Starting offset
        """
        logger.info(
            f"tool=list_issues_with_journals assigned_to_id={assigned_to_id} "
            f"project_id={project_id} status_id={status_id} limit={limit}"
        )
        try:
            return _client().list_issues_with_journals(
                assigned_to_id=assigned_to_id,
                project_id=project_id,
                status_id=status_id,
                limit=limit,
                offset=offset,
            )
        except RedmineError as e:
            logger.error(f"list_issues_with_journals error: {e}")
            raise
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 burden of behavioral disclosure. It mentions the tool returns 'a list of issues with all comments' and includes pagination parameters (limit/offset), but doesn't disclose important behavioral traits like whether this is a read-only operation, authentication requirements, rate limits, error conditions, or what happens when parameters are omitted. The description adds minimal context beyond the basic function.

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 front-loaded: the first sentence states the core purpose, followed by a brief use case, then parameter documentation in a clear Args section. Every sentence earns its place, though the structure could be slightly more polished (e.g., separating the use case from the parameter documentation more clearly).

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 the tool has 5 parameters, no annotations, and an output schema exists, the description is moderately complete. It documents all parameters well but lacks behavioral context (permissions, side effects, error handling). The existence of an output schema means the description doesn't need to explain return values, but for a list operation with filtering capabilities, more guidance on usage versus siblings would improve completeness.

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?

With 0% schema description coverage, the description compensates well by documenting all 5 parameters with clear semantics: it explains what each parameter represents (e.g., 'Assignee ID (obtain via list_users)', 'Status ID or "open" / "closed" / "*"'), provides practical guidance on defaults and constraints (e.g., 'all projects if omitted', 'max 100'), and clarifies parameter behavior beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool 'Returns a list of issues with all comments' and mentions it's 'Useful for reviewing progress per assignee', providing a specific verb+resource+scope. However, it doesn't explicitly differentiate from sibling tools like 'list_issues' or 'search_issues_full', which likely offer different filtering or output capabilities.

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 like 'list_issues' or 'search_issues_full'. It mentions the tool is 'useful for reviewing progress per assignee', which implies a use case but doesn't offer explicit when/when-not instructions or name alternative tools for different scenarios.

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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