Done Bear

Add Comment

comment_add

Post a comment on a task. It is attributed to the connected user and is visible to everyone in the workspace, so write it as a message to the user's teammates rather than as a note to the user. Nobody is notified: a comment is read when someone opens the task.

Input Schema

TableJSON Schema

Name	Required	Description
`body`	Yes	Comment text
`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
`idempotency_key`	No	Stable key that makes retries safe: repeated calls with the same key create only one record and return the same id.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`id`	Yes
`ok`	Yes
`taskId`	Yes

TDQS

A4.7/5.0

Behavior5/5

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

The description goes beyond the sparse annotations (readOnlyHint=false, destructiveHint=false) by disclosing that the comment is attributed to the connected user, visible to everyone in the workspace, and that nobody is notified. It even advises writing as a message to teammates. This is valuable behavioral context for an AI agent deciding how to write the comment.

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?

Three purposeful sentences with no filler. The action is front-loaded, followed by high-impact guidance on attribution, visibility, and notifications. 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?

For a relatively simple add-comment tool with a fully documented schema and an output schema, the description covers all critical behavioral aspects: what is posted, who sees it, who it is attributed to, and who gets notified. No essential information is missing.

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 description coverage is 100%, so the baseline is 3. The description adds meaning beyond the schema by specifying the tone and audience for the body parameter ('write it as a message to the user's teammates rather than as a note to the user'), which directly informs how to construct the body value. No explicit parameter-by-parameter mapping, but enough added semantics to raise the score.

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 opens with a specific verb and resource: 'Post a comment on a task.' This clearly distinguishes comment_add from its CRUD siblings like comment_edit, comment_list, and comment_remove. The added context about visibility and notifications further clarifies what the operation does.

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 opening sentence 'Post a comment on a task' clearly frames when this tool is appropriate. It also gives context about audience and notification behavior. However, it does not explicitly contrast with comment_edit or comment_remove, nor does it state when not to use this tool, so it falls short of a 5.

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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