plan_from_contexts

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 mentions AI usage, which hints at potential non-deterministic or resource-intensive behavior, but doesn't specify details like rate limits, authentication needs, output format, or whether it's a read-only or mutative operation. The description is too brief to adequately cover behavioral traits beyond the basic purpose.

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, efficient sentence that directly states the tool's purpose. It's appropriately sized and front-loaded with the core action, though it could be slightly more informative without sacrificing brevity. There's no wasted text, making it concise and well-structured.

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 complexity of AI-based planning with contexts, the description is incomplete. No annotations exist to clarify behavior, and there's no output schema to describe return values. The description doesn't explain what 'actionable plans' entail, how results are formatted, or any dependencies on other tools. This leaves significant gaps for an agent to understand the tool's full context and usage.

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?

Schema description coverage is 100%, so the schema already documents both parameters ('context_ids' and 'planning_prompt') with descriptions and constraints. The tool description adds no additional meaning about parameters beyond what the schema provides, such as explaining what 'contexts' are or how the prompt influences planning. This meets the baseline for high 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 'Analyze contexts and generate actionable plans using AI' states a clear purpose with a verb ('analyze' and 'generate') and resource ('contexts'), but it's somewhat vague about what 'contexts' are and doesn't distinguish this tool from siblings like 'consolidate_contexts' or 'search_contexts' that might also involve context analysis. It specifies AI involvement, which adds some differentiation.

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 doesn't mention prerequisites, such as needing existing contexts from tools like 'create_context' or 'list_contexts', or when to prefer this over other planning-related tools (if any exist). Usage is implied only by the tool name and description, with no explicit context or exclusions.

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