Append a learning record

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

Annotations already cover the basic mutation profile (not read-only, not idempotent, not destructive). The description adds meaningful behavioral context beyond those annotations: source-visible material never changes mastery state, which clarifies the tool's side effects on learning state and is not derivable from the schema or 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?

Two sentences with no filler. The primary action is front-loaded, and the important behavioral caveat about mastery state is placed second, following naturally from the action.

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?

The description is adequate for a straightforward append operation, and the schema covers required fields and constraints. Still, it does not clarify what happens for closed-book versus source-visible entries beyond the one guarantee, nor what the operation returns, which leaves some practical ambiguity for an agent.

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. It adds meaning for 'kind' by enumerating the four values and for 'source_visibility' by explaining the mastery-state implication. However, it does not clarify 'node_id', 'content', or the optional 'sources' array, leaving significant parameter semantics to the schema alone.

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 states a specific verb ('Append') and resource ('to a node'), and enumerates the exact kinds of content: note, reflection, source, or exercise. It also adds a distinguishing scoping rule about source-visible material, which helps separate it from related learning-state tools.

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 implies when to use the tool—when appending learning material to a node—and its note that source-visible material never changes mastery state hints at one selection criterion. However, it does not explicitly name alternatives like update_node_learning_state or record_verification, nor state when not to use this tool.

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