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jira_add_comment

Add comments to Jira issues to provide updates, share information, or document progress on tasks and tickets.

Instructions

Add a comment to a Jira issue

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
issue_keyYesIssue key (e.g., PROJ-123)
commentYesComment text

Implementation Reference

  • The handler function that executes the jira_add_comment tool. It extracts issue_key and comment from arguments, calls the Jira client's issue_add_comment method, and returns a success message.
    async def _add_comment(self, arguments: dict) -> List[TextContent]:
        """Add a comment to an issue"""
        issue_key = arguments["issue_key"]
        comment = arguments["comment"]
        
        self.jira_client.issue_add_comment(issue_key, comment)
        
        return [TextContent(
            type="text",
            text=f"Added comment to issue: {issue_key}"
        )]
  • Input schema defining the parameters for the jira_add_comment tool: issue_key (string) and comment (string), both required.
    inputSchema={
        "type": "object",
        "properties": {
            "issue_key": {
                "type": "string",
                "description": "Issue key (e.g., PROJ-123)"
            },
            "comment": {
                "type": "string",
                "description": "Comment text"
            }
        },
        "required": ["issue_key", "comment"]
    }
  • Registers the jira_add_comment tool with the MCP server by including it in the list_tools() response, specifying name, description, and input schema.
    Tool(
        name="jira_add_comment",
        description="Add a comment to a Jira issue",
        inputSchema={
            "type": "object",
            "properties": {
                "issue_key": {
                    "type": "string",
                    "description": "Issue key (e.g., PROJ-123)"
                },
                "comment": {
                    "type": "string",
                    "description": "Comment text"
                }
            },
            "required": ["issue_key", "comment"]
        }
    ),
  • Dispatches the tool call to the _add_comment handler function in the call_tool method.
    elif name == "jira_add_comment":
        return await self._add_comment(arguments)
Behavior2/5

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

With no annotations provided, the description carries full burden but only states the basic action without behavioral details. It doesn't disclose if this requires specific permissions, rate limits, whether comments are editable/deletable, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with zero wasted words—it directly states the tool's purpose without redundancy or fluff. This makes it highly efficient and front-loaded for quick comprehension.

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

Completeness2/5

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 no annotations and no output schema, the description is incomplete. It lacks crucial context like authentication needs, error handling, return values, or how it differs from sibling tools, leaving the agent under-informed for effective use.

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?

Schema description coverage is 100%, with both parameters ('issue_key' and 'comment') clearly documented in the schema. The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints, so it meets the baseline for adequate but unenhanced coverage.

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 action ('Add a comment') and target resource ('to a Jira issue'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its siblings like 'jira_update_issue' or 'jira_transition_issue' which might also involve modifying issues, missing an opportunity for clearer distinction.

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. It doesn't mention prerequisites (e.g., needing issue access), exclusions (e.g., not for private comments), or comparisons to siblings like 'jira_update_issue' for other modifications, leaving the agent without contextual usage cues.

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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