get_my_workAsk what you should be doing, rather than reading the whole board and guessing. Returns the tasks assigned to you, what is currently claimed, and — most importantly — how much finished work is already waiting on the human. If that queue is full, the honest answer is to help clear it rather than start something new, and this tells you so before you pick.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many tasks to return (default 5) |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true and destructiveHint=false, so the description need not repeat that. It adds useful behavioral context: it tells the agent how to prioritize (clear the human queue) and that the tool reveals queue status. This goes beyond annotations and helps the agent act appropriately.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loads the primary benefit, and includes actionable guidance in a natural way. It could be slightly tighter, but every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool is read-only, has a simple optional parameter fully covered by schema, and no output schema or nested objects, the description is complete. It tells the agent what to expect (tasks assigned, claimed, and waiting) and how to use the result, leaving no critical gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter (limit) has 100% schema coverage with a clear description, so the schema already explains it. The description does not add extra semantics for this parameter, but that is acceptable given the coverage. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns tasks assigned to the user, currently claimed work, and finished work waiting on the human. It does not explicitly name a sibling tool, but the purpose is specific and distinguishable from list_tasks and get_board_state.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description advises using this tool instead of 'reading the whole board and guessing', implying when to use it. It also gives strategic guidance on when not to start new work (if the human queue is full). It does not mention specific sibling alternatives, but the context is clear.
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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