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Add Comment

jira_add_comment
Destructive

Adds a comment to a Jira issue using Markdown. Optionally set visibility or mark as customer-visible for JSM issues.

Instructions

Add a comment to a Jira issue.

Args: ctx: The FastMCP context. issue_key: Jira issue key. body: Comment text in Markdown. visibility: (Optional) Comment visibility as JSON string. public: (Optional) For JSM issues. True = customer-visible, False = internal/agent-only. Uses ServiceDesk API.

Returns: JSON string representing the added comment object.

Raises: ValueError: If in read-only mode or Jira client unavailable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
issue_keyYesJira issue key (e.g., 'PROJ-123', 'ACV2-642')
bodyYesComment text in Markdown format
visibilityNo(Optional) Comment visibility as JSON string (e.g. '{"type":"group","value":"jira-users"}')
publicNo(Optional) For JSM/Service Desk issues only. Set to true for customer-visible comment, false for internal agent-only comment. Uses the ServiceDesk API (plain text, not Markdown). Cannot be combined with visibility.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

The description adds value beyond annotations by detailing behavior: it notes read-only mode raises ValueError, explains the conditional ServiceDesk API usage for the public parameter, and states the return type as JSON string. Annotations only have destructiveHint=true, so the description significantly enhances 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 succinct with clear sections for Args, Returns, and Raises. Every sentence is informative and free of redundancy. At 7 lines, it is appropriately sized and front-loaded with the primary purpose.

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

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 4 parameters (2 required) and an output schema (though not shown), the description covers behavior, error cases, and return type. It does not detail the exact JSON return structure but that is likely in the output schema. Overall, it is sufficiently complete for correct usage.

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 detailed descriptions for each parameter. The tool description adds minimal new meaning beyond the schema, mostly restating parameter purposes. Baseline score of 3 is appropriate as schema carries the burden.

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 explicitly states 'Add a comment to a Jira issue', which is a clear verb+resource combination. It distinguishes itself from siblings like 'jira_edit_comment' and 'confluence_add_comment' by specifying Jira and adding a new comment.

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?

While the description explains parameter usage (visibility vs public), it does not explicitly state when to use this tool over alternatives like 'jira_edit_comment' for editing or 'confluence_add_comment' for Confluence. Usage context is implied but not directly contrasted.

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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