create_goal_treePersist an observable learning goal as branches with prerequisite-linked knowledge nodes, defining outcomes and importance to structure what must be learned.
Persist one observable goal, its branches, and prerequisite-linked knowledge nodes. Search first. Use reuse_node_id only for truly equivalent existing concepts.
| Name | Required | Description | Default |
|---|---|---|---|
| goal | Yes | ||
| branches | Yes |
Changes observed during successful MCP inspections.
v0.1.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate this is not read-only and not idempotent, so 'Persist' is consistent. The description adds valuable behavioral context beyond annotations: search first to avoid duplicatesainer, and only reuse truly equivalent concepts. It does not contradict the annotations.
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 two sentences with three distinct, compact instructions: persist, search first, and only reuse when truly equivalent. Every clause earns its place and the most important action is front-loaded.
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?
For a complex nested tool with no output schema, the description gives the essential search-reuse workflow and the core persistence action. However, it omits return/error expectations and does not clarify what 'minimal sufficient' means in practice, so it is adequate but not fully complete for invoking the tool correctly.
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 0%, so the description must compensate for parameter meaning, but it only offers conceptual labels like 'goal,' 'branches,' and 'prerequisite-linked knowledge nodes.' It does not explain the required fields, temp_id linkage, or how to construct a valid nested goal tree, leaving the agent without enough parameter-level guidance.
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 opens with 'Persist one observable goal, its branches, and prerequisite-linked knowledge nodes,' a specific verb+resource statement that clearly communicates what the tool creates. This distinguishes it from sibling read, update, diagnose, and export tools even without opening the schema.
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 explicitly says 'Search first,' establishing a clear precondition to search the knowledge base before persisting a goal tree. The reuse_node_id guidance adds a useful when-to-reuse rule, though it does not name sibling tools directly or fully spell out when-not-to-use alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.