forest_overviewAssess learning progress by reading goals, mastery counts, and next ready nodes. Use this non-modifying overview to plan what to study next.
Read goals, mastery counts, and the next ready knowledge nodes. Call this first; it never modifies learning state.
| Name | Required | Description | Default |
|---|---|---|---|
| goal_id | No | Optional goal ID to scope the overview. |
Changes observed during successful MCP inspections.
v0.1.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the 'never modifies learning state' statement is largely redundant. The description does add useful context about what content is read, but no new behavioral traits beyond the annotations are disclosed.
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 short, front-loaded sentences with no wasted words. It states the return content and the invocation guidance in an efficient, easily parseable way.
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 simple read-only tool with one optional parameter and no output schema, the description is complete. It tells the agent what the tool does, what it returns, when to call it, and confirms it is safe to invoke.
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 coverage is 100%, and the single optional goal_id parameter is already described in the schema. The description adds no further parameter-level guidance, so the baseline 3 is appropriate.
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 uses a specific verb ('Read') and names the exact resources it returns: goals, mastery counts, and next ready knowledge nodes. This clearly distinguishes it from sibling tools like search_knowledge or get_learning_queue, which address different concerns.
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 instructs to 'call this first', giving actionable routing guidance for an agent. It does not name alternatives or exclusions, but the first-call directive and read-only emphasis provide enough context for correct selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.