Done Bear

List Task Comments

comment_list

Read-only

Read the comment thread on a task, oldest first, with each comment's id, author and whether it has been edited. Comments are the discussion around a task; the task's own notes are where its content belongs.

Input Schema

TableJSON Schema

Name	Required	Description
`task`	Yes	Workspace-scoped task number, encoded as a string
`context`	Yes	Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization."
`workspace`	No	Workspace id, slug, or name

Output Schema

TableJSON Schema

Name	Required	Description
`count`	Yes
`total`	Yes
`taskId`	Yes
`hasMore`	Yes	True when more results matched than were returned
`comments`	Yes

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already indicate a read-only, non-destructive operation, and the description adds useful behavioral detail beyond that: results are ordered oldest first and include each comment's id, author, and edited status. This is meaningful context for an agent deciding whether the returned data will satisfy the user's request.

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 compact and front-loaded: the first sentence states the operation and key output details, and the second sentence provides valuable semantic context without redundancy. Every sentence earns its place.

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

Completeness5/5

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

Given the read-only annotations, fully documented parameters, and presence of an output schema, the description provides all essential context an agent needs to invoke and interpret the tool. It covers the purpose, output ordering, and conceptual distinction from task notes.

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 parameters are fully documented in the schema itself. The description does not need to restate parameter meanings, and it adds no additional parameter-level detail beyond tying the operation to a specific task's comment thread.

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 clearly states the specific action ('Read the comment thread on a task') and the resource, while also defining the output fields and ordering. It also distinguishes comments from task notes, making it easy to identify what this tool is for relative to siblings like comment_add and task_show.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides helpful context for when to use the tool: comments are the discussion around a task, while the task's own notes are for content. It does not explicitly name an alternative tool, but the semantic distinction strongly guides selection without being misleading.

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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TDQS

A3.6/5.0

Disambiguation4/5

Tools are grouped cleanly by resource (task, checklist, comment, label, project, attachment), so most actions have an obvious owner. The main ambiguities are task_list vs. search and checklist_done vs. checklist_edit, but the descriptions call out the intended boundaries clearly enough to avoid frequent misselection.

Naming Consistency4/5

The dominant resource_verb pattern (task_add, task_edit, checklist_list, comment_remove, project_join) is consistent and predictable. A few outliers like get_context, guide, search, and task_attachment_list break the pattern, but the naming remains readable and mostly uniform.

Tool Count2/5

At 35 tools, this is a very large surface for an agent to choose from and exceeds the 25-tool threshold where count becomes a liability. The tools are well organized, but the repeated verb families across six resources make the total feel heavy even though each tool is plausibly justified.

Completeness4/5

The core task lifecycle is well covered: create, show, edit, list, complete, reopen, archive, assign, and bulk operations, plus full checklist, comment, label, and attachment workflows. Notable gaps are the lack of an explicit unarchive/restore path and no label edit/delete, but these are minor enough that agents can usually work around them.

Resources

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