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atlassian-mcp__jira_add_comment

Add a comment to a Jira issue.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "issue_key": "<issue_key>",
      "comment": "<comment>"
    },
    "name": "atlassian-mcp__jira_add_comment"
  }
}

Input Schema

NameRequiredDescriptionDefault
accountNoOptional email address of the connected account to use (e.g. 'user@gmail.com'). If omitted, the default account is used.
commentYesComment text (plain text, will be converted to ADF)
issue_keyYesThe issue key (e.g. PROJ-123)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=false and destructiveHint=false, so the write-but-non-destructive profile is covered structurally. The description adds nothing beyond that: no mention of permission requirements, whether the comment is attributed to the connected account, or what the response contains. For a mutation tool this is a thin disclosure.

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?

A single front-loaded sentence with zero filler. It is efficient, though the brevity reflects under-specification rather than disciplined compression.

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 two-required-parameter write tool with a fully documented schema and safety annotations, the essentials are covered. Gaps remain around permission needs and return value (no output schema), which an agent would need when the call fails or to confirm success.

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%, so the schema already explains issue_key format, plain-text-to-ADF conversion, and the optional account selector. The description adds no parameter meaning, so the baseline of 3 applies.

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?

States a specific verb ('Add') and resource ('a comment to a Jira issue'), which cleanly distinguishes it from jira_edit_comment, jira_delete_comment, and confluence_add_comment. It does not explicitly name those siblings, but the verb+resource combination is unambiguous.

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?

No guidance on when to use this versus jira_edit_comment (for existing comments) or confluence_add_comment (for the other product). The agent must infer the routing from the tool name alone; there is no stated prerequisite such as needing an existing issue key or prior read of the issue.

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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