Skip to main content
Glama

confluence_get_comments

Retrieve all comments associated with a Confluence page using its numeric page ID for analysis or review.

Instructions

Get comments for a specific Confluence page.

Args: ctx: The FastMCP context. page_id: Confluence page ID.

Returns: JSON string representing a list of comment objects.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
page_idYesConfluence page ID (numeric ID, can be parsed from URL, e.g. from 'https://example.atlassian.net/wiki/spaces/TEAM/pages/123456789/Page+Title' -> '123456789')

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations provided, so the description must carry the burden. It mentions the return format as 'JSON string representing a list of comment objects' but fails to disclose behaviors like error handling, rate limits, or authentication needs. For a simple read operation, minimal transparency is provided.

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 concise and well-structured, with a clear sentence for purpose and a parameter block. No unnecessary information; every sentence serves a 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 an output schema exists, the description's mention of return format is sufficient. The param is well-covered. However, it lacks usage context and error scenarios, but for a straightforward GET operation, it is reasonably complete.

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?

Schema coverage is 100% with a clear description of page_id, including a helpful note on parsing it from a URL. The description adds practical context beyond the schema, aiding the agent in correct parameter usage.

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 'Get comments for a specific Confluence page,' specifying the verb and resource. It distinguishes from sibling tools like 'confluence_get_page' and 'confluence_get_labels' by targeting comments, though it doesn't explicitly contrast with 'confluence_add_comment'.

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 tool versus alternatives, such as other comment retrieval methods. No prerequisites or exclusions mentioned. The description merely states the function without usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/SharkyND/mcp-atlassian'

If you have feedback or need assistance with the MCP directory API, please join our Discord server