Done Bear

Search Tasks

search

Read-only

Search tasks across the workspace. Ranked lexical search over title and description: exact and prefix matches rank first, then word-boundary, substring, and fuzzy matches, with recency and status factored in. Multi-word queries match in any order.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	Max results
`query`	Yes	Search query (matches title and description)
`state`	No	Filter by task state	all
`cursor`	No	Opaque pagination cursor from a previous call's `nextCursor`. Pass it with the same filters to fetch the next page.
`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."
`timezone`	No	IANA timezone used to resolve "today" for views and scheduling (e.g. Australia/Melbourne). Defaults to UTC, which misclassifies Today/Upcoming for users in other timezones, so always pass the user's timezone when known.
`workspace`	No	Workspace id, slug, or name

Output Schema

TableJSON Schema

Name	Required	Description
`count`	Yes
`query`	Yes
`tasks`	Yes
`total`	Yes
`hasMore`	Yes	True when more results matched than were returned
`nextCursor`	Yes

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already mark the tool as read-only and non-destructive. The description adds meaningful behavioral detail beyond that: exact and prefix matches rank first, then word-boundary, substring, and fuzzy matches, with recency and status factored in, and multi-word queries match in any order. This helps the agent set expectations about result relevance.

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 core action and scope appear in the first sentence, followed by two dense but relevant sentences about ranking behavior. No words are wasted.

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?

The description is sufficient for a read-only search tool with full schema documentation and an output schema. It does not mention pagination or timezone handling, but the schema already documents cursor and timezone clearly, so there is no critical gap for the agent to invoke the tool correctly.

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 value by explaining how the query parameter behaves semantically: it searches title and description, uses a ranked matching order, and treats multi-word queries as order-insensitive. This goes beyond the schema's basic 'matches title and description' text.

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: 'Search tasks across the workspace.' It then clarifies the specialized matching semantics (ranked lexical search over title and description), which distinguishes it from siblings like task_list or 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 Guidelines3/5

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

The intended use case is implied rather than explicitly stated: it is a search tool, so agents can infer when to use it. However, the description does not name alternatives like task_list or task_show, nor does it state when to prefer search over structured listing or detail retrieval.

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

All Done Bear tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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

Need Help?