get_next_task

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool provides 'AI-powered recommendations' but doesn't clarify key behavioral aspects: whether it's a read-only operation, how it handles missing data, if it requires specific permissions, what the output format looks like, or any rate limits. For a tool with 10 parameters and no output schema, this lack of detail is a significant gap.

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 a single, well-structured sentence that efficiently conveys the core purpose without unnecessary words. It's front-loaded with the main action ('Get AI-powered recommendations') and includes key contextual elements. However, it could be slightly more concise by avoiding the repetition of 'based on' phrasing, but overall it's appropriately sized for the tool's complexity.

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's complexity (10 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral traits, parameter meanings, output format, and usage guidelines. While it states the purpose clearly, it doesn't provide enough context for an agent to effectively select and invoke this tool, especially compared to siblings with similar functions like 'plan_sprint'.

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 schema description coverage is 0%, meaning none of the 10 parameters are documented in the schema. The description mentions general factors like 'priorities, dependencies, team capacity, and current project state', which loosely map to some parameters (e.g., 'teamSkills', 'sprintCapacity', 'currentPhase'), but it doesn't explain what individual parameters do, their expected formats, or how they influence the recommendations. This fails to compensate for the poor schema coverage.

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 the tool's purpose: 'Get AI-powered recommendations for the next task to work on based on priorities, dependencies, team capacity, and current project state.' It specifies the verb ('Get AI-powered recommendations') and resource ('next task'), and mentions key factors like priorities and dependencies. However, it doesn't explicitly distinguish this from sibling tools like 'plan_sprint' or 'analyze_task_complexity', which might have overlapping functionality.

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 provides no guidance on when to use this tool versus alternatives. It mentions factors like 'priorities, dependencies, team capacity, and current project state' but doesn't specify scenarios where this tool is preferred over siblings such as 'plan_sprint' or 'get_current_iteration'. There's no mention of prerequisites, exclusions, or typical use cases, leaving the agent with minimal contextual direction.

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